iDVEIP: A computer-aided approach for the prediction of viral entry inhibitory peptides

With the notable surge in therapeutic peptide development, various peptides have emerged as potential agents against virus-induced diseases. Viral entry inhibitory peptides (VEIPs), a subset of antiviral peptides (AVPs), offer a promising avenue as entry inhibitors (EIs) with distinct advantages over chemical counterparts. Despite this, a comprehensive analytical platform for characterizing these peptides and their effectiveness in blocking viral entry remains lacking. In this study, we introduce a groundbreaking in silico approach that leverages bioinformatics analysis and machine learning to characterize and identify novel VEIPs. Cross-validation results demonstrate the efficacy of a model combining sequence-based features in predicting VEIPs with high accuracy, validated through independent testing. Additionally, an EI type model has been developed to distinguish peptides specifically acting as Eis from AVPs with alternative activities. Notably, we present iDVEIP, a web-based tool accessible at http://mer.hc.mmh.org.tw/iDVEIP/, designed for automatic analysis and prediction of VEIPs. Emphasizing its capabilities, the tool facilitates comprehensive analyses of peptide characteristics, providing detailed amino acid composition data for each prediction. Furthermore, we showcase the tool's utility in identifying EIs against severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2).

Unprecedented dengue outbreak in Taiwan following COVID-19

Present study reports an unprecedented dengue outbreak in Taiwan post-COVID-19. Interrupted time series analysis reveals a significant surge after easing restrictions, emphasizing the roles of COVID-19 measures, especially travel restrictions, international transportation and climate change in the epidemic. Preventing and controlling dengue remain substantial challenges in the post-COVID-19 era.

Development of an Albumin-Masked mutPD-1Ig as a Tumor Lesion-Selective Immune Checkpoint Inhibitor

The antitumor effects elicited by immune checkpoint inhibitors (ICIs) have transformed cancer treatments. However, severe immune-related adverse events (irAEs) resulting from these treatments have restricted the application of ICIs. To overcome the adverse events, we developed a tumor lesion-selective pro-PD-1Ig that is activated by proteases overexpressed in tumors. We genetically linked albumin to the N-terminus of a modified PD-1Ig (termed mutPD-1Ig hereafter) via an MMP substrate sequence to form Alb-hinge-mutPD-1Ig. We demonstrate that the binding activity of nondigested Alb-hinge-mutPD-1Ig is approximately 11-folds lower than mutPD-1Ig. However, digestion by type IV collagenase restored the binding activity of Alb-hinge-mutPD-1Ig to a level comparable to that of native mutPD-1Ig. In order to enhance the masking efficiency of Alb-mutPD-1Ig, we simulated the effects of diverse MMP substrate linkers for connecting albumin and PD-1 at various starting positions by bioinformatics tools. Our validation experiments indicate Alb-hinge-mutPD-1Ig displayed the best masking efficiency among all simulated constructs. Our study suggests that albumin may be best applicable to mask a target protein whose binding motif is centralized and in the proximity of the N-terminus of the protein.

The Effectiveness of Bivalent COVID-19 Vaccination: A Preliminary Report

Vaccination has been a game-changer in the long battle against COVID-19. However, waning vaccine-induced immunity and the immune evasion of emerging variants create challenges. The rapid-fire development of bivalent vaccines (BVs), comprising ancestral strains and a new variant, was authorized to prevent COVID-19, but the effectiveness of the updated vaccines remains largely unclear. Electronic databases were searched to investigate the immunogenicity and reactogenicity of BVs in humans. As of March 2023, 20 trials were identified. Compared with monovalent vaccination, the induced immunogenicity against ancestral strains was similar. The BVs demonstrated approximately 33-50% higher immunogenicity values against additional variant strains. An observational cohort study showed the additional clinical effectiveness of the BVs. The adverse events were similar. In conclusion, our systematic review found that the BVs had equal immunogenicity against ancestral strains without safety concerns. Approximately 33-50% increased additional antibody titers and clinical effectiveness against additional variant strains were observed in subjects with a BV vaccine with moderate heterogeneity, especially for BA.1-containing BVs.

Microbiome analysis of maternal and neonatal microbial communities associated with the different delivery modes based on 16S rRNA gene amplicon sequencing

OBJECTIVE

With the rising number of cases of non-vaginal delivery worldwide, scientists have been concerned about the influence of the different delivery modes on maternal and neonatal microbiomes. Although the birth rate trend is decreasing rapidly in Taiwan, more than 30 percent of newborns are delivered by caesarean section every year. However, it remains unclear whether the different delivery modes could have a certain impact on the postpartum maternal microbiome and whether it affects the mother-to-newborn vertical transmission of bacteria at birth.

MATERIALS AND METHODS

To address this, we recruited 30 mother-newborn pairs to participate in this study, including 23 pairs of vaginal delivery (VD) and seven pairs of caesarean section (CS). We here investigate the development of the maternal prenatal and postnatal microbiomes across multiple body habitats. Moreover, we also explore the early acquisition of neonatal gut microbiome through a vertical multi-body site microbiome analysis.

RESULTS AND CONCLUSION

The results indicate that no matter the delivery mode, it only slightly affects the maternal microbiome in multiple body habitats from pregnancy to postpartum. On the other hand, about 95% of species in the meconium microbiome were derived from one of the maternal body habitats; notably, the infants born by caesarean section acquire bacterial communities resembling their mother's oral microbiome. Consequently, the delivery modes play a crucial role in the initial colonization of the neonatal gut microbiome, potentially impacting children's health and development.

To PCR or not? The impact of shifting policy from PCR to rapid antigen tests to diagnose COVID-19 during the omicron epidemic: a nationwide surveillance study

Background

Coronavirus disease 2019 (COVID-19) had caused huge impacts worldwide. Polymerase chain reaction (PCR) is the mainstay diagnostic modality. In most hospitals in Taiwan, samples for PCR are collected at emergency department (ER) or outdoor clinics to avoid virus spread inside hospitals. Home rapid antigen test (RAT) is a feasible, low-cost, and convenient tool with moderate sensitivity and high specificity, which can be performed at home to reduce hospital visits. Due to comparably low severity of omicron variant and high vaccine coverage (~80% residents fully vaccinated with AstraZeneca, Moderna, or Pfizer BioNTech COVID-19 vaccines as of March 2022), the policy was shifted from containment to co-existing with COVID-19 in Taiwan. Virus spread rapidly in the community after the ease of social restrictive measurements. To acquire a confirmed diagnosis, PCR testing was requested for people with suspected COVID-19 infection. As a consequence, people with respiratory symptoms or contact history surged into hospitals for PCR testing, thus, the medical capacity was challenged. The diagnostic policy was altered from PCR to RAT, but the impact of diagnostic policy change remains unclear.

Objectives

We conducted this study to investigate the number of COVID-19 cases, PCR testing, hospitalizations, mortalities, and hospital visits during the epidemic and evaluate the impact of diagnostic policy change on hospital visits.

Methods

The diagnostic policy change was implemented in late May 2022. We used nationwide and hospital-based data of COVID-19 cases, PCR testing, hospitalizations, mortalities, and hospital visits before and after policy change as of 31 Jul 2022.

Results

During the omicron epidemic, significant and synchronous increase of COVID-19 patients, PCR testing, hospital visits were observed. COVID-19 cases increased exponentially since April 2022 and the COVID-19 patients peaked in June (1,943, 55,571, and 61,511 average daily new cases in April, May, and June, respectively). The PCR testing peaked in May (85,788 daily tests) with high positive rate (81%). The policy of RAT as confirmatory diagnosis was implemented on 26 May 2022 and a substantial decline of PCR testing numbers occurred (85,788 and 83,113 daily tests in May and June). People hospitalized for COVID-19 peaked in June (821.8 patients per day) and decreased in July (549.5 patients). The mortality cases also peaked in June (147 cases/day). This trend was also validated by the hospital-based data with a significant decrease of emergency department visits (11,397 visits in May while 8,126 visits in June) and PCR testing (21,314 in May and 6,158 in June). The proportion of people purely for PCR testing also decreased (10-26 vs. 5-14%, before and after policy change, respectively).

Conclusions

The impact of diagnostic policy change was a complicated issue and our study demonstrated the huge impact of diagnostic policy on health seeking behavior. The PCR testing numbers and emergency department visits had substantial decrease after diagnostic policy change, and the plateau of epidemic peak eased gradually in ~1 month later. Widespread RAT application may contribute to the decreased hospital visits and preserve medical capacity. Our study provides some evidences for policy maker's reference.

Low-level mosaic trisomy 13 at amniocentesis in a pregnancy associated with a favorable fetal outcome and cytogenetic discrepancy in various tissues

OBJECTIVE

We present low-level mosaic trisomy 13 at amniocentesis in a pregnancy associated with associated with a favorable fetal outcome and cytogenetic discrepancy in various tissues.

CASE REPORT

A 38-year-old, gravida 3, para 0, woman underwent amniocentesis at 19 weeks of gestation because of advanced maternal age. This pregnancy was conceived by in vitro fertilization and embryo transfer. Amniocentesis revealed a karyotype of 47,XX,+13[2]/ 46,XX[20] in co-twin A and a karyotype of 46,XY in co-twin B. In co-twin A, among 22 colonies of cultured amniocytes, two colonies had a karyotype of 47,XX,+13, whereas the rest 20 colonies had the karyotype of 46,XX. Array comparative genomic hybridization (aCGH) analysis on the DNA extracted from cultured amniocytes revealed arr (1-22,X) × 2, Y × 0 and detected no genomic imbalance. Prenatal ultrasound and parental karyotypes were normal. Quantitative fluorescence polymerase chain reaction (QF-PCR) analysis on the DNA extracted from the parental bloods and cultured amniocytes excluded uniparental disomy (UPD) 13. The woman was encouraged to continue the pregnancy. At 37 weeks of gestation, a normal 2410-g female co-twin A and a normal 2360-g male co-twin B were delivered without any phenotypic abnormality. The karyotypes of cord blood, umbilical cord and placenta of co-twin A were 46,XX (40/40 cells), 47,XX,+13 [1]/46,XX[39] and 47,XX,+13[36]/46,XX [4], respectively. QF-PCR analysis on cord blood of co-twin A excluded UPD 13. When follow-up at age 1½ years, the neonate of co-twin A was normal in physical and psychomotor development.

CONCLUSION

Low-level true mosaic trisomy 13 at amniocentesis can be associated with a favorable fetal outcome and cytogenetic discrepancy in various tissues.

A flexible liposomal polymer complex as a platform of specific and regulable immune regulation for individual cancer immunotherapy

BACKGROUND

The applicability and therapeutic efficacy of specific personalized immunotherapy for cancer patients is limited by the genetic diversity of the host or the tumor. Side-effects such as immune-related adverse events (IRAEs) derived from the administration of immunotherapy have also been observed. Therefore, regulatory immunotherapy is required for cancer patients and should be developed.

METHODS

The cationic lipo-PEG-PEI complex (LPPC) can stably and irreplaceably adsorb various proteins on its surface without covalent linkage, and the bound proteins maintain their original functions. In this study, LPPC was developed as an immunoregulatory platform for personalized immunotherapy for tumors to address the barriers related to the heterogenetic characteristics of MHC molecules or tumor associated antigens (TAAs) in the patient population. Here, the immune-suppressive and highly metastatic melanoma, B16F10 cells were used to examine the effects of this platform. Adsorption of anti-CD3 antibodies, HLA-A2/peptide, or dendritic cells' membrane proteins (MP) could flexibly provide pan-T-cell responses, specific Th1 responses, or specific Th1 and Th2 responses, depending on the host needs. Furthermore, with regulatory antibodies, the immuno-LPPC complex properly mediated immune responses by adsorbing positive or negative antibodies, such as anti-CD28 or anti-CTLA4 antibodies.

RESULTS

The results clearly showed that treatment with LPPC/MP/CD28 complexes activated specific Th1 and Th2 responses, including cytokine release, CTL and prevented T-cell apoptosis. Moreover, LPPC/MP/CD28 complexes could eliminate metastatic B16F10 melanoma cells in the lung more efficiently than LPPC/MP. Interestingly, the melanoma resistance of mice treated with LPPC/MP/CD28 complexes would be reversed to susceptible after administration with LPPC/MP/CTLA4 complexes. NGS data revealed that LPPC/MP/CD28 complexes could enhance the gene expression of cytokine and chemokine pathways to strengthen immune activation than LPPC/MP, and that LPPC/MP/CTLA4 could abolish the LPPC/MP complex-mediated gene expression back to un-treatment.

CONCLUSIONS

Overall, we proved a convenient and flexible immunotherapy platform for developing personalized cancer therapy.

Associations between Vitamin D Deficiency and Carbohydrate Intake and Dietary Factors in Taiwanese Pregnant Women

This cross-sectional observation study investigated the vitamin D (VD) status in Taiwanese pregnant women and the effects of VD supplementation and macronutrient intake on serum 25-hydroxy-vitamin D (25[OH]D) level. Data on VD intake, daily sunlight exposure, and carbohydrate intake were obtained from 125 pregnant women at 30−37 weeks’ gestation. Serum 25[OH]D level was measured before delivery in all enrolled women; and the mean 25(OH)D level was 43 nmol/L or 17.2 ng/mL. The 25(OH)D level was significantly correlated with total VD intake of pregnant women (r = 0.239; p = 0.007). The severe VD deficiency group (n = 16; mean of 25(OH)D level = 8.5 ng/mL) had significantly lower total VD intake and supplementation than the groups with VD deficiency (n = 69), insufficiency (n = 32), and sufficiency (n = 8). Those with ≥400 IU/day total VD intake (including VD from food and supplementation) had significantly higher 25(OH)D concentration than those with <400 IU/day total VD intake. Those with 400 IU/day VD supplementation could significantly increase serum 25(OH)D concentrations for pregnant women. Among 85 pregnant women with carbohydrate intake of ≥300 g/day, serum 25(OH)D levels were negatively correlated with carbohydrate intake (p = 0.031). In conclusion, VD deficiency was highly prevalent in Taiwanese pregnant women. VD supplementation was the most effective method for increasing 25(OH)D concentration in pregnant women. Higher carbohydrate intake might reduce 25(OH)D levels.

Effects of bamlanivimab alone or in combination with etesevimab on subsequent hospitalization and mortality in outpatients with COVID-19: a systematic review and meta-analysis

Background

Coronavirus disease 2019 (COVID-19) has caused an enormous loss of life worldwide. The spike protein of the severe acute respiratory syndrome coronavirus 2 is the cause of its virulence. Bamlanivimab, a recombinant monoclonal antibody, has been used alone or in combination with etesevimab to provide passive immunity and improve clinical outcomes. A systematic review and meta-analysis was conducted to investigate the therapeutic effects of bamlanivimab with or without etesevimab (BAM/ETE) treatment.

Methods

Our study was registered in PROSPERO (registry number CRD42021270206). We searched the following electronic databases, without language restrictions, until January 2023: PubMed, Embase, medRxiv, and the Cochrane database. A systematic review and meta-analysis was conducted based on the search results.

Results

Eighteen publications with a total of 28,577 patients were identified. Non-hospitalized patients given bamlanivimab with or without etesevimab had a significantly lower risk of subsequent hospitalization (18 trials, odds ratio (OR): 0.37, 95% confidence interval (CI): [0.29-0.49], I²: 69%; p < 0.01) and mortality (15 trials, OR: 0.27, 95% CI [0.17-0.43], I²: 0%; p = 0.85). Bamlanivimab monotherapy also reduced the subsequent risk of hospitalization (16 trials, OR: 0.43, 95% CI [0.34-0.54], I²: 57%; p = 0.01) and mortality (14 trials, OR: 0.28, 95% CI [0.17-0.46], I²: 0%; p = 0.9). Adverse events from these medications were uncommon and tolerable.

Conclusions

In this meta-analysis, we found the use of bamlanivimab with or without etesevimab contributed to a significantly-reduced risk of subsequent hospitalization and mortality in non-hospitalized COVID-19 patients. However, resistance to monoclonal antibodies was observed in COVID-19 variants, resulting in the halting of the clinical use of BAM/ETE. Clinicians' experiences with BAM/ETE indicate the importance of genomic surveillance. BAM/ETE may be repurposed as a potential component of a cocktail regimen in treating future COVID variants.

Transdermal nanolipoplex simultaneously inhibits subcutaneous melanoma growth and suppresses systemically metastatic melanoma by activating host immunity

Benefit for clinical melanoma treatments, the transdermal neoadjuvant therapy could reduce surgery region and increase immunotherapy efficacy. Using lipoplex (Lipo-PEG-PEI-complex, LPPC) encapsulated doxorubicin (DOX) and carrying CpG oligodeoxynucleotide; the transdermally administered nano-liposomal drug complex (LPPC-DOX-CpG) would have high cytotoxicity and immunostimulatory activity to suppress systemic metastasis of melanoma. LPPC-DOX-CpG dramatically suppressed subcutaneous melanoma growth by inducing tumor cell apoptosis and recruiting immune cells into the tumor area. Animal studies further showed that the colonization and growth of spontaneously metastatic melanoma cells in the liver and lung were suppressed by transdermal LPPC-DOX-CpG. Furthermore, NGS analysis revealed IFN-γ and NF-κB pathways were triggered to recruit and activate the antigen-presenting-cells and effecter cells, which could activate the anti-tumor responses as the major mechanism responsible for the therapeutic effect of LPPC-DOX-CpG. Finally, we have successfully proved transdermal LPPC-DOX-CpG as a promising penetrative carrier to activate systemic anti-tumor immunity against subcutaneous and metastatic tumor.

iDVIP: identification and characterization of viral integrase inhibitory peptides

Antiretroviral peptides are a kind of bioactive peptides that present inhibitory activity against retroviruses through various mechanisms. Among them, viral integrase inhibitory peptides (VINIPs) are a class of antiretroviral peptides that have the ability to block the action of integrase proteins, which is essential for retroviral replication. As the number of experimentally verified bioactive peptides has increased significantly, the lack of in silico machine learning approaches can effectively predict the peptides with the integrase inhibitory activity. Here, we have developed the first prediction model for identifying the novel VINIPs using the sequence characteristics, and the hybrid feature set was considered to improve the predictive ability. The performance was evaluated by 5-fold cross-validation based on the training dataset, and the result indicates the proposed model is capable of predicting the VINIPs, with a sensitivity of 85.82%, a specificity of 88.81%, an accuracy of 88.37%, a balanced accuracy of 87.32% and a Matthews correlation coefficient value of 0.64. Most importantly, the model also consistently provides effective performance in independent testing. To sum up, we propose the first computational approach for identifying and characterizing the VINIPs, which can be considered novel antiretroviral therapy agents. Ultimately, to facilitate further research and development, iDVIP, an automatic computational tool that predicts the VINIPs has been developed, which is now freely available at http://mer.hc.mmh.org.tw/iDVIP/.

The impact of COVID-19 on routine vaccinations in Taiwan and an unexpected surge of pneumococcal vaccination

The coronavirus disease 2019 (COVID-19) pandemic has had substantial impacts, including disruptions in routine vaccinations. In Taiwan, COVID-19 was relatively controllable, and the reduction in routine vaccinations was not profound. The impact of the pandemic on vaccination remained unclear. We collected vaccination uptake data at our hospital and analyzed the weekly trends of different vaccines. We calculated the monthly number of vaccinations and compared consumption before and during the COVID-19 pandemic (year 2019 vs years 2020 and 2021). Except for self-paid pneumococcal conjugate vaccines (PCV13), a mild (14.6%, p < .001) monthly decrease in government-funded routine vaccination and a moderate (28.2%, p = .018) monthly decrease in self-paid vaccination were observed during the COVID-19 pandemic. Interestingly, an unexpected surge of PCV13 vaccination occurred with a 355.8% increase. The shortage of COVID-19 vaccines and the potential benefits of PCV13 against COVID-19 may have contributed to this surge. In conclusion, our study found an obvious disruption of vaccination rates in Taiwan during the COVID-19 epidemic. However, an increase in PCV13 vaccination was also observed, and the important role of the infodemic was emphasized.

Effect of Oral Vitamin D3 Supplementation in Exclusively Breastfed Newborns: Prospective, Randomized, Double-Blind, Placebo-Controlled Trial

Exclusively breastfed infants are at a high risk of vitamin D deficiency. Few studies have evaluated the effects of vitamin D supplementation. Hence, we conducted a prospective randomized controlled trial investigating the effects of oral vitamin D3 400 IU/d supplementation in exclusively breastfed newborns. Serum 25-hydroxy-vitamin D (25[OH]D) levels in pregnant women and their newborns were evaluated. Breastfed newborns were randomized to one of two regimens at age 10 days. One group received vitamin D3 supplementation at a dose of 400 IU/d (vD-400 group), whereas the placebo group received a liquid product without vitamin D3. Outcomes were assessed at 4 months of age. A total of 92 pregnant women and their infants were enrolled, and the data of 72 infants (37 in the vD-400 group and 35 in the placebo group) who completed the study at 4 months of age were assessed. The results showed severe vitamin D deficiency in 15.2% of mothers before delivery, while 54.3% had vitamin D deficiency. Moreover, 15.2% of newborns presented with severe vitamin D deficiency at birth, while 52.2% had vitamin D deficiency. Maternal vitamin D levels were significantly correlated with infant vitamin D levels at birth (r = 0.816, p < 0.001). At 4 months of age, weight, head circumference, serum 25(OH)D, phosphorus, and intact parathyroid hormone levels significantly differed between the vD-400 and placebo groups. However, the body length and bone mineral density of the two groups did not differ significantly. Regardless of vitamin D supplementation, participants with severe vitamin D deficiency had significantly higher intact parathyroid hormone levels and lower bone mineral content. In conclusion, among exclusively breastfed infants, oral supplementation with vitamin D3 at a dose of 400 IU/d from age 10 days increased 25(OH)D concentrations at 4 months of age, but it did not affect bone mineralization. © 2022 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).

Anticancer peptide Q7 suppresses the growth and migration of human endometrial cancer by inhibiting DHCR24 expression and modulating the AKT-mediated pathway

Endometrial cancer is one of the most common malignancy affecting women in developed countries. Resection uterus or lesion area is usually the first option for a simple and efficient therapy. Therefore, it is necessary to find a new therapeutic drug to reduce surgery areas to preserve fertility. Anticancer peptides (ACP) are bioactive amino acids with lower toxicity and higher specificity than chemical drugs. This study is to address an ACP, herein named Q7, which could downregulate 24-Dehydrocholesterol Reductase (DHCR24) to disrupt lipid rafts formation, and sequentially affect the AKT signal pathway of HEC-1-A cells to suppress their tumorigenicity such as proliferation and migration. Moreover, lipo-PEI-PEG-complex (LPPC) was used to enhance Q7 anticancer activity in vitro and efficiently show its effects on HEC-1-A cells. Furthermore, LPPC-Q7 exhibited a synergistic effect in combination with doxorubicin or paclitaxel. To summarize, Q7 was firstly proved to exhibit an anticancer effect on endometrial cancer cells and combined with LPPC efficiently improved the cytotoxicity of Q7.

To mix or not to mix? A rapid systematic review of heterologous prime-boost covid-19 vaccination

INTRODUCTION

Coronavirus disease 2019 (COVID-19) has had an enormous impact worldwide, and vaccination is believed to be the method that will control the pandemic. Several types of vaccines developed using different platforms have been authorized, but the immunogenicity and reactogenicity of heterologous prime-boost vaccination with different vaccines remain largely unclear.

AREAS COVERED

Electronic databases including PubMed, Embase, medRxiv, Research Square, and SSRN were searched to investigate the immunogenicity and reactogenicity associated with heterologous vaccination.As of 30 June 2021, four trials including 1,862 participants were identified. Heterologous administration of BNT162b2 (BNT) in ChAdOx1 (ChAd)-primed participants (ChAd/BNT) showed noninferior immunogenicity to homologous BNT administration (both prime and booster were BNT vaccines, BNT/BNT) with tolerable reactogenicity and higher T cell responses. Compared with homologous ChAdOX1 vaccination (ChAd/ChAd), heterologous ChAd/BNT was found to elicit higher immunogenicity (ChAd/BNT vs. ChAd/ChAd, antibody titer ratio: 9.2).

EXPERT OPINION

Our systematic review found robust immunogenicity and tolerable reactogenicity of heterologous administration of a BNT162b2 boost in ChAdOx1-primed participants. An additional benefit of stronger T cellular immunity was also observed. Heterologous vaccination is a reasonable and feasible strategy to combat COVID-19. Further studies are warranted to confirm the benefits and identify the optimal combinations, doses, and intervals.

Repurposing Colchicine in Treating Patients with COVID-19: A Systematic Review and Meta-Analysis

Coronavirus disease 2019 (COVID-19) had caused huge health losses worldwide. Several drugs had been applied to treat patients with COVID-19, and repurposing colchicine had been proposed for its anti-inflammatory properties via several pathways. In this systematic review, we evaluated the effects of colchicine treatment. From inception to May 31, 2021, databases, including PubMed, EMbase, medRxiv, and Research Square were searched, and 11 studies were enrolled. A total of 17,205 COVID-19 patients with male predominance (62.9%) were analyzed. Patients with colchicine treatment had a significantly lower risk of mortality (odds ratio (OR): 0.57, 95% confidence interval (CI): 0.38-0.87, I2: 72%; p < 0.01) and a non-significantly lower rate of mechanical ventilation (OR: 0.67, 95%CI: 0.39-1.15). The side effects were mild and not significantly different (OR: 2.03, 95%CI: 0.51-8.09). Subgroup analysis with randomized controlled trials showed no statistically significant difference in the mortality (OR: 0.80, 95%CI: 0.44-1.46, I2: 33%; p = 0.22). In conclusion, our meta-analysis found that colchicine treatment was associated with a significantly lower risk of mortality in patients with COVID-19. However, this benefit was not observed in the subgroup analysis of randomized controlled trials. Further randomized controlled studies are required to confirm the potential benefits of colchicine treatment.

Identification of subtypes of anticancer peptides based on sequential features and physicochemical properties

Anticancer peptides (ACPs) are a kind of bioactive peptides which could be used as a novel type of anticancer drug that has several advantages over chemistry-based drug, including high specificity, strong tumor penetration capacity, and low toxicity to normal cells. As the number of experimentally verified bioactive peptides has increased significantly, various of in silico approaches are imperative for investigating the characteristics of ACPs. However, the lack of methods for investigating the differences in physicochemical properties of ACPs. In this study, we compared the N- and C-terminal amino acid composition for each peptide, there are three major subtypes of ACPs that are defined based on the distribution of positively charged residues. For the first time, we were motivated to develop a two-step machine learning model for identification of the subtypes of ACPs, which classify the input data into the corresponding group before applying the classifier. Further, to improve the predictive power, the hybrid feature sets were considered for prediction. Evaluation by five-fold cross-validation showed that the two-step model trained with sequence-based features and physicochemical properties was most effective in discriminating between ACPs and non-ACPs. The two-step model trained with the hybrid features performed well, with a sensitivity of 86.75%, a specificity of 85.75%, an accuracy of 86.08%, and a Matthews Correlation Coefficient value of 0.703. Furthermore, the model also consistently provides the effective performance in independent testing set, with sensitivity of 77.6%, specificity of 94.74%, accuracy of 88.99% and the MCC value reached 0.75. Finally, the two-step model has been implemented as a web-based tool, namely iDACP, which is now freely available at http://mer.hc.mmh.org.tw/iDACP/ .

Nanotopography as Artificial Microenvironment for Accurate Visualization of Metastasis Development via Simulation of ECM Dynamics

Metastatic progression is mediated by complex interactions between deregulated extracellular matrix (ECM) and cancer cells and remains a major challenge in cancer management. To investigate the role of ECM dynamics in promoting metastasis development, we developed an artificial microenvironment (AME) platform comprised of nanodot arrays of increasing diameter. Cells cultured on the platform showed increasing signs of mesenchymal-like cell transition as AME diameter increased, suggesting accurate simulation of ECM-mediated gene regulation. Gene expression was analyzed to determine genes significant to transition, which were then used to select appropriate small molecule drugs for time course treatments. Our results suggest that the platform can identify critical target genes as well as possible drug candidates. Overall, the AME platform allows for the study of intricate ECM-induced gene expression trends across metastasis development that would otherwise be difficult to visualize in vivo and may open new avenues toward successful personalized cancer management.

Prenatal diagnosis of mosaicism for trisomy 11 in a single colony at amniocentesis in a pregnancy with a favorable outcome

OBJECTIVE

We present prenatal diagnosis of mosaicism for trisomy 11 in a single colony at amniocentesis with a favorable outcome.

CASE REPORT

A 34-year-old woman underwent amniocentesis at 16 weeks of gestation because of advanced maternal age. Amniocentesis revealed a result of 47,XY,+11[1]/46,XY[9]. In 10 colonies of cultured amniocytes, all five cells in one colony had a karyotype of trisomy 11, while the rest nine colonies had a normal karyotype. The parental karyotypes were normal. Repeat amniocentesis was performed at 19 weeks of gestation. Interphase fluorescence in situ hybridization (FISH) was applied on the uncultured amniocytes, and the result showed no trisomy 11 signals in 56/56 uncultured amniocytes. Uniparental disomy (UPD) 11 was excluded by polymorphic DNA marker analysis. The cultured amniocytes at repeat amniocentesis had a karyotype of 46,XY. Prenatal ultrasound findings were unremarkable. A healthy 3084-g male baby was delivered at 38 weeks of gestation. The karyotype of cord blood lymphocytes was 46,XY. The boy was phenotypically normal at age 10 months at follow-ups. The interphase FISH analysis on urinary cells revealed no trisomy 11 signal.

CONCLUSION

Mosaicism for trisomy 11 in a single colony at amniocentesis without UPD 11 can be associated with a favorable outcome.

iDPGK: characterization and identification of lysine phosphoglycerylation sites based on sequence-based features

Background

Protein phosphoglycerylation, the addition of a 1,3-bisphosphoglyceric acid (1,3-BPG) to a lysine residue of a protein and thus to form a 3-phosphoglyceryl-lysine, is a reversible and non-enzymatic post-translational modification (PTM) and plays a regulatory role in glucose metabolism and glycolytic process. As the number of experimentally verified phosphoglycerylated sites has increased significantly, statistical or machine learning methods are imperative for investigating the characteristics of phosphoglycerylation sites. Currently, research into phosphoglycerylation is very limited, and only a few resources are available for the computational identification of phosphoglycerylation sites.

Result

We present a bioinformatics investigation of phosphoglycerylation sites based on sequence-based features. The TwoSampleLogo analysis reveals that the regions surrounding the phosphoglycerylation sites contain a high relatively of positively charged amino acids, especially in the upstream flanking region. Additionally, the non-polar and aliphatic amino acids are more abundant surrounding phosphoglycerylated lysine following the results of PTM-Logo, which may play a functional role in discriminating between phosphoglycerylation and non-phosphoglycerylation sites. Many types of features were adopted to build the prediction model on the training dataset, including amino acid composition, amino acid pair composition, positional weighted matrix and position-specific scoring matrix. Further, to improve the predictive power, numerous top features ranked by F-score were considered as the final combination for classification, and thus the predictive models were trained using DT, RF and SVM classifiers. Evaluation by five-fold cross-validation showed that the selected features was most effective in discriminating between phosphoglycerylated and non-phosphoglycerylated sites.

Conclusion

The SVM model trained with the selected sequence-based features performed well, with a sensitivity of 77.5%, a specificity of 73.6%, an accuracy of 74.9%, and a Matthews Correlation Coefficient value of 0.49. Furthermore, the model also consistently provides the effective performance in independent testing set, yielding sensitivity of 75.7% and specificity of 64.9%. Finally, the model has been implemented as a web-based system, namely iDPGK, which is now freely available at http://mer.hc.mmh.org.tw/iDPGK/.

Taiwan Government-Guided Strategies Contributed to Combating and Controlling COVID-19 Pandemic

Coronavirus disease 2019 (COVID-19) is highly contagious, and thus has become an emerging health crisis worldwide. The optimal strategies to prevent the spread of this disease are inconclusive, and therefore, the adopted measurements to combat COVID-19 varies in different countries. In mid-March and late-August 2020, we performed internet searches to collect relevant information, from sources such as the website of the World Health Organization. The epidemiological data of COVID-19 from several countries were collected and we found that Taiwan had a comparably successful story for combating the pandemic. As of mid-March, Taiwan had high rates of diagnostic testing (688.5 tests per million citizens) with a lower infection rate (49 cases, 2.1 cases per million people). As of late-August, there were 488 cases (20 cases per million people). Furthermore, Taiwanese government-guided strategies and hospital data were also reviewed. We summarized some important strategies to combat COVID-19, which include: (1) border control; (2) official media channel and press conferences; (3) name-based rationing system for medical masks; (4) TOCC-based rapid triage, outdoor clinics, and protective sampling devices; and (5) social distancing, delaying the start of new semesters, and religious assembly restriction. In conclusion, Taiwan had lower rates of COVID-19 compared with other countries, and Taiwan government-guided strategies contributed to the control of the disease's spread.

Multi-omics profiling reveals microRNA-mediated insulin signaling networks

Background

MicroRNAs (miRNAs) play a key role in mediating the action of insulin on cell growth and the development of diabetes. However, few studies have been conducted to provide a comprehensive overview of the miRNA-mediated signaling network in response to glucose in pancreatic beta cells. In our study, we established a computational framework integrating multi-omics profiles analyses, including RNA sequencing (RNA-seq) and small RNA sequencing (sRNA-seq) data analysis, inverse expression pattern analysis, public data integration, and miRNA targets prediction to illustrate the miRNA-mediated regulatory network at different glucose concentrations in INS-1 pancreatic beta cells (INS-1), which display important characteristics of the pancreatic beta cells.

Results

We applied our computational framework to the expression profiles of miRNA/mRNA of INS-1, at different glucose concentrations. A total of 1437 differentially expressed genes (DEGs) and 153 differentially expressed miRNAs (DEmiRs) were identified from multi-omics profiles. In particular, 121 DEmiRs putatively regulated a total of 237 DEGs involved in glucose metabolism, fatty acid oxidation, ion channels, exocytosis, homeostasis, and insulin gene regulation. Moreover, Argonaute 2 immunoprecipitation sequencing, qRT-PCR, and luciferase assay identified Crem, Fn1, and Stc1 are direct targets of miR-146b and elucidated that miR-146b acted as a potential regulator and promising target to understand the insulin signaling network.

Conclusions

In this study, the integration of experimentally verified data with system biology framework extracts the miRNA network for exploring potential insulin-associated miRNA and their target genes. The findings offer a potentially significant effect on the understanding of miRNA-mediated insulin signaling network in the development and progression of pancreatic diabetes.

A panel of eight microRNAs is a good predictive parameter for triple-negative breast cancer relapse

Rationale: Triple-negative breast cancer (TNBC), which has the highest recurrence rate and shortest survival time of all breast cancers, is in urgent need of a risk assessment method to determine an accurate treatment course. Recently, miRNA expression patterns have been identified as potential biomarkers for diagnosis, prognosis, and personalized therapy. Here, we investigate a combination of candidate miRNAs as a clinically applicable signature that can precisely predict relapse in TNBC patients after surgery. Methods: Four total cohorts of training (TCGA_TNBC and GEOD-40525) and validation (GSE40049 and GSE19783) datasets were analyzed with logistic regression and Gaussian mixture analyses. We established a miRNA signature risk model and identified an 8-miRNA signature for the prediction of TNBC relapse. Results: The miRNA signature risk model identified ten candidate miRNAs in the training set. By combining 8 of the 10 miRNAs (miR-139-5p, miR-10b-5p, miR-486-5p, miR-455-3p, miR-107, miR-146b-5p, miR-324-5p and miR-20a-5p), an accurate predictive model of relapse in TNBC patients was established and was highly correlated with prognosis (AUC of 0.80). Subsequently, this 8-miRNA signature prognosticated relapse in the two validation sets with AUCs of 0.89 and 0.90. Conclusion: The 8-miRNA signature predictive model may help clinicians provide a prognosis for TNBC patients with a high risk of recurrence after surgery and provide further personalized treatment to decrease the chance of relapse.

Lipoplex-based targeted gene therapy for the suppression of tumours with VEGFR expression by producing anti-angiogenic molecules

BACKGROUND

The anti-angiogenic fusion protein RBDV-IgG1 Fc (RBDV), which comprises the receptor-binding domain of vascular endothelial growth factor-A (VEGF-A), has shown antitumour effects by reducing angiogenesis in vivo. This study used the cationic lipoplex lipo-PEG-PEI-complex (LPPC) to simultaneously encapsulate both the RBDV targeting protein and the RBDV plasmid (pRBDV) without covalent bonds to assess VEGFR targeting gene therapy in mice with melanoma in vivo.

RESULTS

LPPC protected the therapeutic transgene from degradation by DNase, and the LPPC/RBDV complexes could specifically target VEGFR-positive B16-F10 cells both in vitro and in vivo. With or without RBDV protein-targeting direction, the pRBDV-expressing RBDV proteins were expressed and reached a maximal concentration on the 7th day in the sera after transfection in vivo and significantly elicited growth suppression against B16-F10 melanoma but not IgG1 control proteins. In particular, LPPC/pRBDV/RBDV treatment with the targeting molecules dramatically inhibited B16-F10 tumour growth in vivo to provide better therapeutic efficacy than the treatments with gene therapy with IgG1 protein targeting or administration of a protein drug with RBDV.

CONCLUSIONS

The simultaneous combination of the LPPC complex with pRBDV gene therapy and RBDV protein targeting might be a potential tool to conveniently administer targeted gene therapy for cancer therapy.

The relationships of genetic polymorphisms of the long noncoding RNA growth arrest-specific transcript 5 with uterine cervical cancer

The purposes of the investigation were to examine the implications of long noncoding RNA growth arrest-specific transcript 5 (GAS5) in progression and clinicopathological factors of uterine cervical cancer, and patient survival in Taiwan. Genotypic distributions of two GAS5 genetic variants rs145204276 and rs55829688 were detected in 208 patients including 111 patients with invasive cancer, 97 with precancerous lesions as well as 307 control women using real-time polymerase chain reaction. It explored that patients with cervical precancerous lesion had lower rate of AGGCA deletion (Del) in both alleles (Del/Del) of GAS5 rs145204276 as compared with control women. Patients with invasive cancer did not exhibit higher rate of Del/Del. Meanwhile, there were no different genotypic distributions in rs55829688 among patients with cervical invasive cancer and those with precancerous lesions as well as control women. Moreover, cervical cancer patients with Ins (insertion, AGGCA)/Del and Del/Del (-/-) in GAS5 rs55829688 tended to have poorer hazard ratio (HR) of 5 years survival. In addition, lymph node metastasis status exerted the most significantly predictive of 5 years survival rate. Conclusively, GAS5 polymorphism rs145204276 is probably applicable to predict 5 years survival HR of cervical cancer patients. However, the mechanism elucidating the methylation status and transcription function of rs145204276 in uterine cervical cancer needs to be delineated for its unique implication in uterine cervical cancer.

Sphingosine-1-phosphate promotes PDGF-dependent endothelial progenitor cell angiogenesis in human chondrosarcoma cells

The malignant bone tumors that are categorized as chondrosarcomas display a high potential for metastasis in late-stage disease. Higher-grade chondrosarcomas contain higher levels of expression of platelet-derived growth factor (PDGF) and its receptor. The phosphorylation of sphingosine by sphingosine kinase enzymes SphK1 and SphK2 generates sphingosine-1-phosphate (S1P), which inhibits human chondrosarcoma cell migration, while SphK1 overexpression suppresses lung metastasis of chondrosarcoma. We sought to determine whether S1P mediates levels of PDGF-A expression and angiogenesis in chondrosarcoma. Surprisingly, our investigations found that treatment of chondrosarcoma cells with S1P and transfecting them with SphK1 cDNA increased PDGF-A expression and induced angiogenesis of endothelial progenitor cells (EPCs). Ras, Raf, MEK, ERK and AP-1 inhibitors and their small interfering RNAs (siRNAs) inhibited S1P-induced PDGF-A expression and EPC angiogenesis. Our results indicate that S1P promotes the expression of PDGF-A in chondrosarcoma via the Ras/Raf/MEK/ERK/AP-1 signaling cascade and stimulates EPC angiogenesis.

miRTarBase update 2018: a resource for experimentally validated microRNA-target interactions

MicroRNAs (miRNAs) are small non-coding RNAs of ∼ 22 nucleotides that are involved in negative regulation of mRNA at the post-transcriptional level. Previously, we developed miRTarBase which provides information about experimentally validated miRNA-target interactions (MTIs). Here, we describe an updated database containing 422 517 curated MTIs from 4076 miRNAs and 23 054 target genes collected from over 8500 articles. The number of MTIs curated by strong evidence has increased ∼1.4-fold since the last update in 2016. In this updated version, target sites validated by reporter assay that are available in the literature can be downloaded. The target site sequence can extract new features for analysis via a machine learning approach which can help to evaluate the performance of miRNA-target prediction tools. Furthermore, different ways of browsing enhance user browsing specific MTIs. With these improvements, miRTarBase serves as more comprehensively annotated, experimentally validated miRNA-target interactions databases in the field of miRNA related research. miRTarBase is available at http://miRTarBase.mbc.nctu.edu.tw/.

Genome-wide discovery of viral microRNAs based on phylogenetic analysis and structural evolution of various human papillomavirus subtypes

In mammals, microRNAs (miRNAs) play key roles in controlling posttranscriptional regulation through binding to the mRNAs of target genes. Recently, it was discovered that viral miRNAs may be involved in human cancers and diseases. It is likely that viral miRNAs help viruses enter the latent phase of their life cycle and become undetected by the host's immune system, while increasing the host's risk for cancer development. Cervical cancer is typically related to the infection of human papillomavirus (HPV) through sexual transmission. To further understand the molecular mechanisms underlying the associations of HPV infection with genital diseases, we developed a systematic method for viral miRNA identification and viral miRNA-mediated regulatory network construction based on genome-wide sequence analysis. The complete genomes of certain high-risk HPV subtypes were used to predict putative viral pre-miRNAs by bioinformatics approaches. In addition, small RNA libraries in human cervical lesions from existing publications were collected to validate the predicted HPV pre-miRNAs. For the construction of virally encoded miRNA-mediated regulatory network of HPV infection, cervical squamous epithelial carcinoma gene expression data were extracted from the RNA sequencing platform in The Cancer Genome Atlas; the differentially expressed genes were used to identify the putative targets of viral miRNAs. Predicted cellular target genes of HPV-encoded miRNAs provide an overview of these viral miRNA's putative functions. Finally, a large-scale genome analysis was carried out to examine the phylogenetic relationship and structural evolution among genital HPV types that have the potential to cause genital cancer. In this study, we discovered putative HPV-encoded miRNAs, which were validated against the small RNA libraries in human cervical lesions. Furthermore, as indicated by their biological functions, host genes targeted by HPV-encoded miRNAs may play significant roles in virus infection and carcinogenesis. These viral miRNAs pose as promising candidates for the development of antiviral drugs. More importantly, the identified subtype-specific miRNAs have the potential to be used as biomarkers for HPV subtype determination.

Resistin Enhances Monocyte Chemoattractant Protein-1 Production in Human Synovial Fibroblasts and Facilitates Monocyte Migration

BACKGROUND/AIMS

The adipocyte-secreting adipokine, resistin, may play a critical role in the modulation of inflammatory diseases. Migration and infiltration of mononuclear cells into inflammatory sites are critical events during the development of osteoarthritis (OA). Monocyte chemoattractant protein-1 (MCP-1), also known as chemokine ligand 2 (CCL2), plays a critical role in the regulation of monocyte migration and infiltration. In this study, we show how resistin promotes MCP-1 expression in OA synovial fibroblasts and monocyte migration.

METHODS

We used qPCR to detect MCP-1 and miRNA expression. THP-1 migration was investigated by Transwell assay. The Western blotting was used to examine the resistinmediated signaling pathways.

RESULTS

Resistin activated the phosphatidylinositol-3-kinase (PI3K), Akt and mammalian target of rapamycin (mTOR) signaling pathways, while PI3K, Akt and mTOR inhibitors or small interfering RNAs diminished resistin-induced MCP-1 expression and monocyte migration. We also demonstrate that resistin stimulates MCP-1mediated monocyte migration by suppressing microRNA (miR)-33a and miR-33b via the PI3K, Akt and mTOR signaling pathways.

CONCLUSION

These results provide new insights into the mechanisms of resistin action that may have therapeutic implications for patients with OA.

Characterization and identification of lysine glutarylation based on intrinsic interdependence between positions in the substrate sites

Background

Glutarylation, the addition of a glutaryl group (five carbons) to a lysine residue of a protein molecule, is an important post-translational modification and plays a regulatory role in a variety of physiological and biological processes. As the number of experimentally identified glutarylated peptides increases, it becomes imperative to investigate substrate motifs to enhance the study of protein glutarylation. We carried out a bioinformatics investigation of glutarylation sites based on amino acid composition using a public database containing information on 430 non-homologous glutarylation sites.

Results

The TwoSampleLogo analysis indicates that positively charged and polar amino acids surrounding glutarylated sites may be associated with the specificity in substrate site of protein glutarylation. Additionally, the chi-squared test was utilized to explore the intrinsic interdependence between two positions around glutarylation sites. Further, maximal dependence decomposition (MDD), which consists of partitioning a large-scale dataset into subgroups with statistically significant amino acid conservation, was used to capture motif signatures of glutarylation sites. We considered single features, such as amino acid composition (AAC), amino acid pair composition (AAPC), and composition of k-spaced amino acid pairs (CKSAAP), as well as the effectiveness of incorporating MDD-identified substrate motifs into an integrated prediction model. Evaluation by five-fold cross-validation showed that AAC was most effective in discriminating between glutarylation and non-glutarylation sites, according to support vector machine (SVM).

Conclusions

The SVM model integrating MDD-identified substrate motifs performed well, with a sensitivity of 0.677, a specificity of 0.619, an accuracy of 0.638, and a Matthews Correlation Coefficient (MCC) value of 0.28. Using an independent testing dataset (46 glutarylated and 92 non-glutarylated sites) obtained from the literature, we demonstrated that the integrated SVM model could improve the predictive performance effectively, yielding a balanced sensitivity and specificity of 0.652 and 0.739, respectively. This integrated SVM model has been implemented as a web-based system (MDDGlutar), which is now freely available at http://csb.cse.yzu.edu.tw/MDDGlutar/.

Electronic supplementary material

The online version of this article (10.1186/s12859-018-2394-9) contains supplementary material, which is available to authorized users.

Gut microbiome changes in overweight male adults following bowel preparation

Background

Human gut microbiome has an essential role in human health and disease. Although the major dominant microbiota within individuals have been reported, the change of gut microbiome caused by external factors, such as antibiotic use and bowel cleansing, remains unclear. We conducted this study to investigate the change of gut microbiome in overweight male adults after bowel preparation, where none of the participants had been diagnosed with any systemic diseases.

Methods

A total of 20 overweight, male Taiwanese adults were recruited, and all participants were omnivorous. The participants provided fecal samples and blood samples at three time points: prior to bowel preparation, 7 days after colonoscopy, and 28 days after colonoscopy. The microbiota composition in fecal samples was analyzed using 16S ribosome RNA gene amplicon sequencing.

Results

Our results demonstrated that the relative abundance of the most dominant bacteria hardly changed from prior to bowel preparation to 28 days after colonoscopy. Using the ratio of Prevotella to the sum of Prevotella and Bacteroides in the fecal samples at baseline, the participants were separated into two groups. The fecal samples of the Type 1 group was Bacteroides-dominant, and that of the Type 2 group was Prevotella-dominant with a noticeable presence Bacteroides. Bulleidia appears more in the Type 1 fecal samples, while Akkermensia appears more in the Type 2 fecal samples. Of each type, the gut microbial diversity differed slightly among the three collection times. Additionally, the Type 2 fecal microbiota was temporarily susceptible to bowel cleansing. Predictive functional analysis of microbial community reveals that their activities for the mineral absorption metabolism and arachidonic acid metabolism differed significantly between the two types. Depending on their fecal type, the variance of triglycerides and C-reactive protein also differed between the two types of participants.

Conclusions

Depending upon the fecal type, the microbial diversity and the predictive functional modules of microbial community differed significantly after bowel preparation. In addition, blood biochemical markers presented somewhat associated with fecal type. Therefore, our results might provide some insights as to how knowledge of the microbial community could be used to promote health through personalized clinical treatment.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-5285-6) contains supplementary material, which is available to authorized users.

Vaginal microbiome variances in sample groups categorized by clinical criteria of bacterial vaginosis

Background

One of the most common and recurrent vaginal infections is bacterial vaginosis (BV). The diagnosis is based on changes to the “normal” vaginal microbiome; however, the normal microbiome appears to differ according to reproductive status and ethnicity, and even among individuals within these groups. The Amsel criteria and Nugent score test are widely used for diagnosing BV; however, these tests are based on different criteria, and so may indicate distinct changes in the vaginal microbial community. Nevertheless, few studies have compared the results of these test against metagenomics analysis.

Methods

Vaginal flora samples from 77 participants were classified according to the Amsel criteria and Nugent score test. The microbiota composition was analyzed using 16S ribosome RNA gene amplicon sequencing. Bioinformatics analysis and multivariate statistical analysis were used to evaluate the microbial diversity and function.

Results

Only 3 % of the participants diagnosed BV negative using the Amsel criteria (A−) were BV-positive according to the Nugent score test (N+), while over half of the BV-positive patients using the Amsel criteria (A+) were BV-negative according to the Nugent score test (N−). Thirteen genera showed significant differences in distribution among BV status defined by BV tests (e.g., A − N−, A + N− and A + N+). Variations in the four most abundant taxa, Lactobacillus, Gardnerella, Prevotella, and Escherichia, were responsible for most of this dissimilarity. Furthermore, vaginal microbial diversity differed significantly among the three groups classified by the Nugent score test (N−, N+, and intermediate flora), but not between the Amsel criteria groups. Numerous predictive microbial functions, such as bacterial chemotaxis and bacterial invasion of epithelial cells, differed significantly among multiple BV test, but not between the A− and A+ groups.

Conclusions

Metagenomics analysis can greatly expand our current understanding of vaginal microbial diversity in health and disease. Metagenomics profiling may also provide more reliable diagnostic criteria for BV testing.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-5284-7) contains supplementary material, which is available to authorized users.

Significant association of long non-coding RNAs HOTAIR genetic polymorphisms with cancer recurrence and patient survival in patients with uterine cervical cancer

Up to date, no study explores the relationship of single nucleotide polymorphisms (SNPs) of long non-coding RNAs HOTAIR (lncRNAs HOTAIR) with cancer recurrence and patient survival in uterine cervical cancer for Taiwanese women. We therefore designed this study to investigate the clinical roles of lncRNAs HOTAIR SNPs in cervical cancer. One hundred and sixteen patients with cervical invasive cancer and 96 patients with preinvasive lesions as well as 318 control women were consecutively recruited. LncRNAs HOTAIR SNPs rs920778, rs12427129, rs4759314 and rs1899663 were analyzed and their genotypic frequencies were examined by real-time polymerase chain reaction. The results indicated that there were no genotypic differences between patients with cervical neoplasia and normal controls as well as among patients with invasive and invasive cancer, and normal controls. However, genotype GG in lncRNAs HOTAIR SNP rs920778 was demonstrated to be a predictor for poorer cancer recurrence probability [p=0.001, hazard ratio (HR): 7.25, 95% CI: 2.19-23.96]. Furthermore, cervical cancer patients with genotype GG in lncRNAs HOTAIR rs920778 had worse overall survival (p =0.002, HR: 7.22, 95% CI: 2.09-24.92). No significant associations exhibited between lncRNAs HOTAIR SNP rs920778 and clinicopathological parameters. In conclusion, this studied lncRNAs HOTAIR SNPs are not associated with cervical carcinongensis. However, lncRNAs HOTAIR SNP rs920778 may be regarded as an independent predictor of cancer recurrence probability and overall survival in cervical cancer patients.

MDD-carb: a combinatorial model for the identification of protein carbonylation sites with substrate motifs

Background

Carbonylation, which takes place through oxidation of reactive oxygen species (ROS) on specific residues, is an irreversibly oxidative modification of proteins. It has been reported that the carbonylation is related to a number of metabolic or aging diseases including diabetes, chronic lung disease, Parkinson’s disease, and Alzheimer’s disease. Due to the lack of computational methods dedicated to exploring motif signatures of protein carbonylation sites, we were motivated to exploit an iterative statistical method to characterize and identify carbonylated sites with motif signatures.

Results

By manually curating experimental data from research articles, we obtained 332, 144, 135, and 140 verified substrate sites for K (lysine), R (arginine), T (threonine), and P (proline) residues, respectively, from 241 carbonylated proteins. In order to examine the informative attributes for classifying between carbonylated and non-carbonylated sites, multifarious features including composition of twenty amino acids (AAC), composition of amino acid pairs (AAPC), position-specific scoring matrix (PSSM), and positional weighted matrix (PWM) were investigated in this study. Additionally, in an attempt to explore the motif signatures of carbonylation sites, an iterative statistical method was adopted to detect statistically significant dependencies of amino acid compositions between specific positions around substrate sites. Profile hidden Markov model (HMM) was then utilized to train a predictive model from each motif signature. Moreover, based on the method of support vector machine (SVM), we adopted it to construct an integrative model by combining the values of bit scores obtained from profile HMMs. The combinatorial model could provide an enhanced performance with evenly predictive sensitivity and specificity in the evaluation of cross-validation and independent testing.

Conclusion

This study provides a new scheme for exploring potential motif signatures at substrate sites of protein carbonylation. The usefulness of the revealed motifs in the identification of carbonylated sites is demonstrated by their effective performance in cross-validation and independent testing. Finally, these substrate motifs were adopted to build an available online resource (MDD-Carb, http://csb.cse.yzu.edu.tw/MDDCarb/) and are also anticipated to facilitate the study of large-scale carbonylated proteomes.

Electronic supplementary material

The online version of this article (10.1186/s12918-017-0511-4) contains supplementary material, which is available to authorized users.

MDD-Palm: Identification of protein S-palmitoylation sites with substrate motifs based on maximal dependence decomposition

S-palmitoylation, the covalent attachment of 16-carbon palmitic acids to a cysteine residue via a thioester linkage, is an important reversible lipid modification that plays a regulatory role in a variety of physiological and biological processes. As the number of experimentally identified S-palmitoylated peptides increases, it is imperative to investigate substrate motifs to facilitate the study of protein S-palmitoylation. Based on 710 non-homologous S-palmitoylation sites obtained from published databases and the literature, we carried out a bioinformatics investigation of S-palmitoylation sites based on amino acid composition. Two Sample Logo indicates that positively charged and polar amino acids surrounding S-palmitoylated sites may be associated with the substrate site specificity of protein S-palmitoylation. Additionally, maximal dependence decomposition (MDD) was applied to explore the motif signatures of S-palmitoylation sites by categorizing a large-scale dataset into subgroups with statistically significant conservation of amino acids. Single features such as amino acid composition (AAC), amino acid pair composition (AAPC), position specific scoring matrix (PSSM), position weight matrix (PWM), amino acid substitution matrix (BLOSUM62), and accessible surface area (ASA) were considered, along with the effectiveness of incorporating MDD-identified substrate motifs into a two-layered prediction model. Evaluation by five-fold cross-validation showed that a hybrid of AAC and PSSM performs best at discriminating between S-palmitoylation and non-S-palmitoylation sites, according to the support vector machine (SVM). The two-layered SVM model integrating MDD-identified substrate motifs performed well, with a sensitivity of 0.79, specificity of 0.80, accuracy of 0.80, and Matthews Correlation Coefficient (MCC) value of 0.45. Using an independent testing dataset (613 S-palmitoylated and 5412 non-S-palmitoylated sites) obtained from the literature, we demonstrated that the two-layered SVM model could outperform other prediction tools, yielding a balanced sensitivity and specificity of 0.690 and 0.694, respectively. This two-layered SVM model has been implemented as a web-based system (MDD-Palm), which is now freely available at http://csb.cse.yzu.edu.tw/MDDPalm/.

Investigation and identification of protein carbonylation sites based on position-specific amino acid composition and physicochemical features

BACKGROUND

Protein carbonylation, an irreversible and non-enzymatic post-translational modification (PTM), is often used as a marker of oxidative stress. When reactive oxygen species (ROS) oxidized the amino acid side chains, carbonyl (CO) groups are produced especially on Lysine (K), Arginine (R), Threonine (T), and Proline (P). Nevertheless, due to the lack of information about the carbonylated substrate specificity, we were encouraged to develop a systematic method for a comprehensive investigation of protein carbonylation sites.

RESULTS

After the removal of redundant data from multipe carbonylation-related articles, totally 226 carbonylated proteins in human are regarded as training dataset, which consisted of 307, 126, 128, and 129 carbonylation sites for K, R, T and P residues, respectively. To identify the useful features in predicting carbonylation sites, the linear amino acid sequence was adopted not only to build up the predictive model from training dataset, but also to compare the effectiveness of prediction with other types of features including amino acid composition (AAC), amino acid pair composition (AAPC), position-specific scoring matrix (PSSM), positional weighted matrix (PWM), solvent-accessible surface area (ASA), and physicochemical properties. The investigation of position-specific amino acid composition revealed that the positively charged amino acids (K and R) are remarkably enriched surrounding the carbonylated sites, which may play a functional role in discriminating between carbonylation and non-carbonylation sites. A variety of predictive models were built using various features and three different machine learning methods. Based on the evaluation by five-fold cross-validation, the models trained with PWM feature could provide better sensitivity in the positive training dataset, while the models trained with AAindex feature achieved higher specificity in the negative training dataset. Additionally, the model trained using hybrid features, including PWM, AAC and AAindex, obtained best MCC values of 0.432, 0.472, 0.443 and 0.467 on K, R, T and P residues, respectively.

CONCLUSION

When comparing to an existing prediction tool, the selected models trained with hybrid features provided a promising accuracy on an independent testing dataset. In short, this work not only characterized the carbonylated substrate preference, but also demonstrated that the proposed method could provide a feasible means for accelerating preliminary discovery of protein carbonylation.

Haptoglobin expression correlates with tumor differentiation and five-year overall survival rate in hepatocellular carcinoma

Elevated serum haptoglobin (Hp) is identified as a prognostic marker in multiple types of solid tumors, which is correlated with poor prognosis. HCC is one of the major causes of cancer deaths in worldwide, which remains poor prognosis and is clinically urgent for discovering early diagnostic markers. However, except for serum Hp, the correlation of tumor Hp expression with hepatocellular carcinoma (HCC) progression is still unclear. In this study, we evaluated and identified the tissue Hp expression as a prognostic marker to predict the survival rate of HCC patients. To evaluate the prognostic value of Hp expression for HCC, two cohorts were enrolled in our study, including total 130 matched pair tissue sections (both adjacent non-tumorous and tumor tissue derived from same patient) of HCC patients from Changhua Christian Hospital (CCH) and total 316 RNA-seq data with clinical information of HCC patients from The Cancer Genome Atlas (TCGA) database. In contrast to other types of cancers, HCC tumor tissues have lower Hp protein expression in CCH cohort and have lower Hp mRNA expression in TCGA cohort as compared with adjacent non-tumorous tissues (p < 0.001). Moreover, lower Hp expression is significantly correlated with different stages of HCC cancer differentiation in CCH cohort (one-way ANOVA, p < 0.001). Most importantly, lower Hp expression is highly correlated with poor five-year overall survival rate in TCGA cohort (p < 0.01). Based on our data, we conclude that tissue Hp expression positively correlates with better HCC tumor differentiation and increased five-year overall survival rate of HCC patients. The results indicated that tissue Hp is potentially a prognostic marker for HCC patients. Our findings may further provide a new insight of effective treatments along with biopsy diagnosis of HCC patients.

Diversity and enterotype in gut bacterial community of adults in Taiwan

Background

Gastrointestinal microbiota, particularly gut microbiota, is associated with human health. The biodiversity of gut microbiota is affected by ethnicities and environmental factors such as dietary habits or medicine intake, and three enterotypes of the human gut microbiome were announced in 2011. These enterotypes are not significantly correlated with gender, age, or body weight but are influenced by long-term dietary habits. However, to date, only two enterotypes (predominantly consisting of Bacteroides and Prevotella) have shown these characteristics in previous research; the third enterotype remains ambiguous. Understanding the enterotypes can improve the knowledge of the relationship between microbiota and human health.

Results

We obtained 181 human fecal samples from adults in Taiwan. Microbiota compositions were analyzed using next-generation sequencing (NGS) technology, which is a culture-independent method of constructing microbial community profiles by sequencing 16S ribosomal DNA (rDNA). In these samples, 17,675,898 sequencing reads were sequenced, and on average, 215 operational taxonomic units (OTUs) were identified for each sample. In this study, the major bacteria in the enterotypes identified from the fecal samples were Bacteroides, Prevotella, and Enterobacteriaceae, and their correlation with dietary habits was confirmed. A microbial interaction network in the gut was observed on the basis of the amount of short-chain fatty acids, pH value of the intestine, and composition of the bacterial community (enterotypes). Finally, a decision tree was derived to provide a predictive model for the three enterotypes. The accuracies of this model in training and independent testing sets were 97.2 and 84.0%, respectively.

Conclusions

We used NGS technology to characterize the microbiota and constructed a predictive model. The most significant finding was that Enterobacteriaceae, the predominant subtype, could be a new subtype of enterotypes in the Asian population.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-3261-6) contains supplementary material, which is available to authorized users.

SOHSite: incorporating evolutionary information and physicochemical properties to identify protein S-sulfenylation sites

Background

Protein S-sulfenylation is a type of post-translational modification (PTM) involving the covalent binding of a hydroxyl group to the thiol of a cysteine amino acid. Recent evidence has shown the importance of S-sulfenylation in various biological processes, including transcriptional regulation, apoptosis and cytokine signaling. Determining the specific sites of S-sulfenylation is fundamental to understanding the structures and functions of S-sulfenylated proteins. However, the current lack of reliable tools often limits researchers to use expensive and time-consuming laboratory techniques for the identification of S-sulfenylation sites. Thus, we were motivated to develop a bioinformatics method for investigating S-sulfenylation sites based on amino acid compositions and physicochemical properties.

Results

In this work, physicochemical properties were utilized not only to identify S-sulfenylation sites from 1,096 experimentally verified S-sulfenylated proteins, but also to compare the effectiveness of prediction with other characteristics such as amino acid composition (AAC), amino acid pair composition (AAPC), solvent-accessible surface area (ASA), amino acid substitution matrix (BLOSUM62), position-specific scoring matrix (PSSM), and positional weighted matrix (PWM). Various prediction models were built using support vector machine (SVM) and evaluated by five-fold cross-validation. The model constructed from hybrid features, including PSSM and physicochemical properties, yielded the best performance with sensitivity, specificity, accuracy and MCC measurements of 0.746, 0.737, 0.738 and 0.337, respectively. The selected model also provided a promising accuracy (0.693) on an independent testing dataset. Additionally, we employed TwoSampleLogo to help discover the difference of amino acid composition among S-sulfenylation, S-glutathionylation and S-nitrosylation sites.

Conclusion

This work proposed a computational method to explore informative features and functions for protein S-sulfenylation. Evaluation by five-fold cross validation indicated that the selected features were effective in the identification of S-sulfenylation sites. Moreover, the independent testing results demonstrated that the proposed method could provide a feasible means for conducting preliminary analyses of protein S-sulfenylation. We also anticipate that the uncovered differences in amino acid composition may facilitate future studies of the extensive crosstalk among S-sulfenylation, S-glutathionylation and S-nitrosylation.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-2299-1) contains supplementary material, which is available to authorized users.

UbiSite: incorporating two-layered machine learning method with substrate motifs to predict ubiquitin-conjugation site on lysines

Background

The conjugation of ubiquitin to a substrate protein (protein ubiquitylation), which involves a sequential process – E1 activation, E2 conjugation and E3 ligation, is crucial to the regulation of protein function and activity in eukaryotes. This ubiquitin-conjugation process typically binds the last amino acid of ubiquitin (glycine 76) to a lysine residue of a target protein. The high-throughput of mass spectrometry-based proteomics has stimulated a large-scale identification of ubiquitin-conjugated peptides. Hence, a new web resource, UbiSite, was developed to identify ubiquitin-conjugation site on lysines based on large-scale proteome dataset.

Results

Given a total of 37,647 ubiquitin-conjugated proteins, including 128026 ubiquitylated peptides, obtained from various resources, this study carries out a large-scale investigation on ubiquitin-conjugation sites based on sequenced and structural characteristics. A TwoSampleLogo reveals that a significant depletion of histidine (H), arginine (R) and cysteine (C) residues around ubiquitylation sites may impact the conjugation of ubiquitins in closed three-dimensional environments. Based on the large-scale ubiquitylation dataset, a motif discovery tool, MDDLogo, has been adopted to characterize the potential substrate motifs for ubiquitin conjugation. Not only are single features such as amino acid composition (AAC), positional weighted matrix (PWM), position-specific scoring matrix (PSSM) and solvent-accessible surface area (SASA) considered, but also the effectiveness of incorporating MDDLogo-identified substrate motifs into a two-layered prediction model is taken into account. Evaluation by five-fold cross-validation showed that PSSM is the best feature in discriminating between ubiquitylation and non-ubiquitylation sites, based on support vector machine (SVM). Additionally, the two-layered SVM model integrating MDDLogo-identified substrate motifs could obtain a promising accuracy and the Matthews Correlation Coefficient (MCC) at 81.06 % and 0.586, respectively. Furthermore, the independent testing showed that the two-layered SVM model could outperform other prediction tools, reaching at 85.10 % sensitivity, 69.69 % specificity, 73.69 % accuracy and the 0.483 of MCC value.

Conclusion

The independent testing result indicated the effectiveness of incorporating MDDLogo-identified motifs into the prediction of ubiquitylation sites. In order to provide meaningful assistance to researchers interested in large-scale ubiquitinome data, the two-layered SVM model has been implemented onto a web-based system (UbiSite), which is freely available at http://csb.cse.yzu.edu.tw/UbiSite/. Two cases given in the UbiSite provide a demonstration of effective identification of ubiquitylation sites with reference to substrate motifs.

Electronic supplementary material

The online version of this article (doi:10.1186/s12918-015-0246-z) contains supplementary material, which is available to authorized users.

A new scheme to discover functional associations and regulatory networks of E3 ubiquitin ligases

Background

Protein ubiquitination catalyzed by E3 ubiquitin ligases play important modulatory roles in various biological processes. With the emergence of high-throughput mass spectrometry technology, the proteomics research community embraced the development of numerous experimental methods for the determination of ubiquitination sites. The result is an accumulation of ubiquitinome data, coupled with a lack of available resources for investigating the regulatory networks among E3 ligases and ubiquitinated proteins. In this study, by integrating existing ubiquitinome data, experimentally validated E3 ligases and established protein-protein interactions, we have devised a strategy to construct a comprehensive map of protein ubiquitination networks.

Results

In total, 41,392 experimentally verified ubiquitination sites from 12,786 ubiquitinated proteins of humans have been obtained for this study. Additional 494 E3 ligases along with 1220 functional annotations and 28588 protein domains were manually curated. To characterize the regulatory networks among E3 ligases and ubiquitinated proteins, a well-established network viewer was utilized for the exploration of ubiquitination networks from 40892 protein-protein interactions. The effectiveness of the proposed approach was demonstrated in a case study examining E3 ligases involved in the ubiquitination of tumor suppressor p53. In addition to Mdm2, a known regulator of p53, the investigation also revealed other potential E3 ligases that may participate in the ubiquitination of p53.

Conclusion

Aside from the ability to facilitate comprehensive investigations of protein ubiquitination networks, by integrating information regarding protein-protein interactions and substrate specificities, the proposed method could discover potential E3 ligases for ubiquitinated proteins. Our strategy presents an efficient means for the preliminary screen of ubiquitination networks and overcomes the challenge as a result of limited knowledge about E3 ligase-regulated ubiquitination.

Electronic supplementary material

The online version of this article (doi:10.1186/s12918-015-0244-1) contains supplementary material, which is available to authorized users.

CircNet: a database of circular RNAs derived from transcriptome sequencing data

Circular RNAs (circRNAs) represent a new type of regulatory noncoding RNA that only recently has been identified and cataloged. Emerging evidence indicates that circRNAs exert a new layer of post-transcriptional regulation of gene expression. In this study, we utilized transcriptome sequencing datasets to systematically identify the expression of circRNAs (including known and newly identified ones by our pipeline) in 464 RNA-seq samples, and then constructed the CircNet database (http://circnet.mbc.nctu.edu.tw/) that provides the following resources: (i) novel circRNAs, (ii) integrated miRNA-target networks, (iii) expression profiles of circRNA isoforms, (iv) genomic annotations of circRNA isoforms (e.g. 282 948 exon positions), and (v) sequences of circRNA isoforms. The CircNet database is to our knowledge the first public database that provides tissue-specific circRNA expression profiles and circRNA-miRNA-gene regulatory networks. It not only extends the most up to date catalog of circRNAs but also provides a thorough expression analysis of both previously reported and novel circRNAs. Furthermore, it generates an integrated regulatory network that illustrates the regulation between circRNAs, miRNAs and genes.

A two-layered machine learning method to identify protein O-GlcNAcylation sites with O-GlcNAc transferase substrate motifs

Protein O-GlcNAcylation, involving the β-attachment of single N-acetylglucosamine (GlcNAc) to the hydroxyl group of serine or threonine residues, is an O-linked glycosylation catalyzed by O-GlcNAc transferase (OGT). Molecular level investigation of the basis for OGT's substrate specificity should aid understanding how O-GlcNAc contributes to diverse cellular processes. Due to an increasing number of O-GlcNAcylated peptides with site-specific information identified by mass spectrometry (MS)-based proteomics, we were motivated to characterize substrate site motifs of O-GlcNAc transferases. In this investigation, a non-redundant dataset of 410 experimentally verified O-GlcNAcylation sites were manually extracted from dbOGAP, OGlycBase and UniProtKB. After detection of conserved motifs by using maximal dependence decomposition, profile hidden Markov model (profile HMM) was adopted to learn a first-layered model for each identified OGT substrate motif. Support Vector Machine (SVM) was then used to generate a second-layered model learned from the output values of profile HMMs in first layer. The two-layered predictive model was evaluated using a five-fold cross validation which yielded a sensitivity of 85.4%, a specificity of 84.1%, and an accuracy of 84.7%. Additionally, an independent testing set from PhosphoSitePlus, which was really non-homologous to the training data of predictive model, was used to demonstrate that the proposed method could provide a promising accuracy (84.05%) and outperform other O-GlcNAcylation site prediction tools. A case study indicated that the proposed method could be a feasible means of conducting preliminary analyses of protein O-GlcNAcylation and has been implemented as a web-based system, OGTSite, which is now freely available at http://csb.cse.yzu.edu.tw/OGTSite/.

miRTarBase 2016: updates to the experimentally validated miRNA-target interactions database

MicroRNAs (miRNAs) are small non-coding RNAs of approximately 22 nucleotides, which negatively regulate the gene expression at the post-transcriptional level. This study describes an update of the miRTarBase (http://miRTarBase.mbc.nctu.edu.tw/) that provides information about experimentally validated miRNA-target interactions (MTIs). The latest update of the miRTarBase expanded it to identify systematically Argonaute-miRNA-RNA interactions from 138 crosslinking and immunoprecipitation sequencing (CLIP-seq) data sets that were generated by 21 independent studies. The database contains 4966 articles, 7439 strongly validated MTIs (using reporter assays or western blots) and 348 007 MTIs from CLIP-seq. The number of MTIs in the miRTarBase has increased around 7-fold since the 2014 miRTarBase update. The miRNA and gene expression profiles from The Cancer Genome Atlas (TCGA) are integrated to provide an effective overview of this exponential growth in the miRNA experimental data. These improvements make the miRTarBase one of the more comprehensively annotated, experimentally validated miRNA-target interactions databases and motivate additional miRNA research efforts.

CircNet: a database of circular RNAs derived from transcriptome sequencing data

Circular RNAs (circRNAs) represent a new type of regulatory noncoding RNA that only recently has been identified and cataloged. Emerging evidence indicates that circRNAs exert a new layer of post-transcriptional regulation of gene expression. In this study, we utilized transcriptome sequencing datasets to systematically identify the expression of circRNAs (including known and newly identified ones by our pipeline) in 464 RNA-seq samples, and then constructed the CircNet database (http://circnet.mbc.nctu.edu.tw/) that provides the following resources: (i) novel circRNAs, (ii) integrated miRNA-target networks, (iii) expression profiles of circRNA isoforms, (iv) genomic annotations of circRNA isoforms (e.g. 282 948 exon positions), and (v) sequences of circRNA isoforms. The CircNet database is to our knowledge the first public database that provides tissue-specific circRNA expression profiles and circRNA–miRNA-gene regulatory networks. It not only extends the most up to date catalog of circRNAs but also provides a thorough expression analysis of both previously reported and novel circRNAs. Furthermore, it generates an integrated regulatory network that illustrates the regulation between circRNAs, miRNAs and genes.

MethHC: a database of DNA methylation and gene expression in human cancer

We present MethHC (http://MethHC.mbc.nctu.edu.tw), a database comprising a systematic integration of a large collection of DNA methylation data and mRNA/microRNA expression profiles in human cancer. DNA methylation is an important epigenetic regulator of gene transcription, and genes with high levels of DNA methylation in their promoter regions are transcriptionally silent. Increasing numbers of DNA methylation and mRNA/microRNA expression profiles are being published in different public repositories. These data can help researchers to identify epigenetic patterns that are important for carcinogenesis. MethHC integrates data such as DNA methylation, mRNA expression, DNA methylation of microRNA gene and microRNA expression to identify correlations between DNA methylation and mRNA/microRNA expression from TCGA (The Cancer Genome Atlas), which includes 18 human cancers in more than 6000 samples, 6548 microarrays and 12 567 RNA sequencing data.

Bacterial communities in semen from men of infertile couples: metagenomic sequencing reveals relationships of seminal microbiota to semen quality

Some previous studies have identified bacteria in semen as being a potential factor in male infertility. However, only few types of bacteria were taken into consideration while using PCR-based or culturing methods. Here we present an analysis approach using next-generation sequencing technology and bioinformatics analysis to investigate the associations between bacterial communities and semen quality. Ninety-six semen samples collected were examined for bacterial communities, measuring seven clinical criteria for semen quality (semen volume, sperm concentration, motility, Kruger's strict morphology, antisperm antibody (IgA), Atypical, and leukocytes). Computer-assisted semen analysis (CASA) was also performed. Results showed that the most abundant genera among all samples were Lactobacillus (19.9%), Pseudomonas (9.85%), Prevotella (8.51%) and Gardnerella (4.21%). The proportion of Lactobacillus and Gardnerella was significantly higher in the normal samples, while that of Prevotella was significantly higher in the low quality samples. Unsupervised clustering analysis demonstrated that the seminal bacterial communities were clustered into three main groups: Lactobacillus, Pseudomonas, and Prevotella predominant group. Remarkably, most normal samples (80.6%) were clustered in Lactobacillus predominant group. The analysis results showed seminal bacteria community types were highly associated with semen health. Lactobacillus might not only be a potential probiotic for semen quality maintenance, but also might be helpful in countering the negative influence of Prevotella and Pseudomonas. In this study, we investigated whole seminal bacterial communities and provided the most comprehensive analysis of the association between bacterial community and semen quality. The study significantly contributes to the current understanding of the etiology of male fertility.

A systematic review of microRNA expression profiling studies in human gastric cancer

Gastric cancer (GC) is the second leading cause of global cancer mortality. Most GC patients are diagnosed with advanced-stage disease and show extremely poor prognosis. All of the GC research has a common interest to search for the specific and sensitive biomarkers for early diagnosis of GC. Number of microRNAs play important role in GC. We carried out a systematic review of published miRNA profiling studies that compared the miRNA expression profiles between GC tissues and paired noncancerous gastric tissue. A vote-counting strategy was followed with the collection of information like total number of studies reporting differential expression of miRNA, total number of tissue samples used in the studies, direction of differential expression and fold change. A total of 352 differentially expressed microRNAs were reported in the 14 microRNA expression profiling studies that compared GC tissues with normal tissues with 120 microRNAs reported at least in two studies. In the group of consistently reported microRNAs, miR-21 was reported upregulated in 10 studies followed by miR-25, miR-92, and miR-223 upregulated in eight studies. MiR-375 and miR-148a were found downregulated in six and five studies, respectively, followed by miR-638 in four studies. MiR-107 and miR-103 were reported in nine and eight studies, respectively, but their expression were inconsistent. From this study, the most consistently reported upregulated microRNA was found to be miR-21. This systematic review study of human GC microRNA expression profiling studies would provide information on microRNAs with potential role as the biomarkers in gastric cancer.

Clinical detection of human probiotics and human pathogenic bacteria by using a novel high-throughput platform based on next generation sequencing

BACKGROUND

The human body plays host to a vast array of bacteria, found in oral cavities, skin, gastrointestinal tract and the vagina. Some bacteria are harmful while others are beneficial to the host. Despite the availability of many methods to identify bacteria, most of them are only applicable to specific and cultivable bacteria and are also tedious. Based on high throughput sequencing technology, this work derives 16S rRNA sequences of bacteria and analyzes probiotics and pathogens species.

RESULTS

We constructed a database that recorded the species of probiotics and pathogens from literature, along with a modified Smith-Waterman algorithm for assigning the taxonomy of the sequenced 16S rRNA sequences. We also constructed a bacteria disease risk model for seven diseases based on 98 samples. Applicability of the proposed platform is demonstrated by collecting the microbiome in human gut of 13 samples.

CONCLUSIONS

The proposed platform provides a relatively easy means of identifying a certain amount of bacteria and their species (including uncultivable pathogens) for clinical microbiology applications. That is, detecting how probiotics and pathogens inhabit humans and how affect their health can significantly contribute to develop a diagnosis and treatment method.