ggVennDiagram: An Intuitive, Easy-to-Use, and Highly Customizable R Package to Generate Venn Diagram

Collagen type V alpha 2 promotes the development of gastric cancer via M2 macrophage polarization

Gastric cancer is a type of digestive tract cancer with a high morbidity and mortality, which leads to a major health burden worldwide. More research into the functions of the immune system will improve therapy and survival in gastric cancer patients. We attempted to identify potential biomarkers or targets in gastric cancer via bioinformatical analysis approaches. Three gene expression profile datasets (GSE79973, GSE103236, and GSE118916) of gastric tissue samples were obtained from the Gene Expression Omnibus database. There were 65 overlapping differentially expressed genes (DEGs) identified from three microarrays. Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway were carried out for the key functions and pathways enriched in the DEGs. Then, ten hub genes were identified by protein-protein interaction network. In addition, we observed that collagen type V alpha 2 (COL5A2) was linked to gastric cancer prognosis as well as M2 macrophage infiltration. Furthermore, COL5A2 enhanced gastric cancer cell proliferation through the PI3K-AKT signaling pathway and polarized M2 macrophage cells. Therefore, in this study, we found that COL5A2 was associated with the development of gastric cancer which might function as a potential therapeutic target for the disease.

Systematic analysis of cancer-specific synthetic lethal interactions provides insight into personalized anticancer therapy

The concept of synthetic lethality has great potential for anticancer therapy as a new strategy to specifically kill cancer cells while sparing normal cells. To further understand the potential molecular interactions and gene characteristics involved in synthetic lethality, we performed a comprehensive analysis of predicted cancer-specific genetic interactions. Many genes were identified as cancer-associated genes that contributed to multiple biological processes and pathways, and the gene features were not random, indicating their potential roles in human carcinogenesis. Some relevant genes detected in multiple cancers were prone to be enriched in specific biological progresses and pathways, especially processes associated with DNA damage, chromosome-related functions and cancer pathways. These findings strongly implicated potential roles for these genes in cancer pathophysiology and functional relationships, as well as applications for future anticancer drug discovery. Further experimental validation indicated that the synthetic lethal interaction of APC and GFER may provide a potential anticancer strategy for patients with APC-mutant colon cancer. These results will contribute to further exploration of synthetic lethal interactions and broader application of the concept of synthetic lethality in anticancer therapeutics.

FLI1 and FRA1 transcription factors drive the transcriptional regulatory networks characterizing muscle invasive bladder cancer

Bladder cancer is mostly present in the form of urothelium carcinoma, causing over 150,000 deaths each year. Its histopathological classification as muscle invasive (MIBC) and non-muscle invasive (NMIBC) is the most prominent aspect, affecting the prognosis and progression of this disease. In this study, we defined the active regulatory landscape of MIBC and NMIBC cell lines using H3K27ac ChIP-seq and used an integrative approach to combine our findings with existing data. Our analysis revealed FRA1 and FLI1 as two critical transcription factors differentially regulating MIBC regulatory landscape. We show that FRA1 and FLI1 regulate the genes involved in epithelial cell migration and cell junction organization. Knock-down of FRA1 and FLI1 in MIBC revealed the downregulation of several EMT-related genes such as MAP4K4 and FLOT1. Further, ChIP-SICAP performed for FRA1 and FLI1 enabled us to infer chromatin binding partners of these transcription factors and link this information with their target genes. Finally, we show that knock-down of FRA1 and FLI1 result in significant reduction of invasion capacity of MIBC cells towards muscle microenvironment using IC-CHIP assays. Our results collectively highlight the role of these transcription factors in selection and design of targeted options for treatment of MIBC.

A bioinformatics approach to identifying the biomarkers and pathogenesis of major depressive disorder combined with acute myocardial infarction

This study investigated the pathogenesis of major depressive disorder (MDD) and acute myocardial infarction (AMI) using bioinformatics. We analyzed MDD and AMI (MDD-AMI) datasets provided by the Gene Expression Omnibus (GEO) database for genes common to MDD and AMI using GEO2R and weighted gene co-expression network analysis (WGCNA). We also performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses, and we used Disease Ontology (DO) analysis to identify a) the pathways through which genes function and b) comorbidities. We also created a protein-protein interaction (PPI) network using the STRING database to identify the hub genes and biomarkers. NetworkAnalyst 3.0 was used to construct a transcription factor (TF) gene regulatory network. We also identified relevant complications and potential drug candidates. The 27 genes common to MDD and AMI were enriched in the pathways regulating TFs and mediating immunity and inflammation. The hub genes in the PPI network included TLR2, HP, ICAM1, LCN2, LTF, VCAN, S100A9 and NFKBIA. Key TFs were KLF9, KLF11, ZNF24, and ZNF580. Cardiovascular, pancreatic, and skeletal diseases were common complications. Hydrocortisone, simvastatin, and estradiol were candidate treatment drugs. Identification of these genes and their pathways may provide new targets for further research on the pathogenesis, biomarkers, and treatment of MDD-AMI. Together our results suggested that TLR2 and VCAN might be the key genes associated with MDD complicated by AMI.

Kluyveromyces marxianus Ameliorates High-Fat-Diet-Induced Kidney Injury by Affecting Gut Microbiota and TLR4/NF-κB Pathway in a Mouse Model

Objectives. The effects of Kluyveromyces marxianus on high-fat diet- (HFD-) induced kidney injury (KI) were explored. Methods. HFD-induced KI model was established using male C57BL/6 mice and treated with K. marxianus JLU-1016 and acid-resistant (AR) strain JLU-1016A. Glucose tolerance was evaluated via an oral glucose tolerance test (OGTT). KI was measured using Hematoxylin and Eosin (H&E) staining and terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) analysis. The chemical indexes were analyzed, including lipid profiles, inflammatory cytokines, and creatinine. The levels of Toll-like receptor 4 (TLR4)/nuclear factor kappa B (NF-κB) or phospho-NF-κB p65 (Ser536) and alpha inhibitor of NF-κB (IκBα) were measured using qPCR and Western blot. The gut microbiota was sequenced using high-throughput sequencing. Results. HFD induction increased OGTT value, KI severity, oxidative stress, inflammatory cytokines, oxidative stress, apoptotic rate, creatinine levels, and the expression of TLR4/NF-κB, phospho-NF-κB p65 (Ser536), and IκBα deteriorated lipid profiles ( $P<0.05$ ) and reduced gut microbiota abundance. K. marxianus treatment ameliorated HFD-induced metabolic disorders and reversed these parameters ( $P<0.05$ ). Compared with the control, HFD induction increased the proportion of Firmicutes but reduced the proportion of Bacteroidetes and Lactobacillus. K. marxianus JLU-1016 and AR strain JLU-1016A treatments improved gut microbiota by reducing the proportion of Firmicutes and increasing the proportion of Bacteroidetes and Lactobacillus in the KI model ( $P<0.0001$ ). Helicobacter has been identified with many infectious diseases and was increased after HFD induction and inhibited after K. marxianus JLU-1016 and AR strain JLU-1016A treatments. The strain JLU-1016A exhibited better results possibly with acid-tolerance properties to pass through an acidic environment of the stomach. Conclusions. K. marxianus may have a beneficial effect on KI by improving gut microbiota and inhibiting TLR4/NF-κB pathway activation.

Histone bivalency regulates the timing of cerebellar granule cell development

Developing neurons undergo a progression of morphological and gene expression changes as they transition from neuronal progenitors to mature, multipolar neurons. Here we use RNA-seq and H3K4me3 and H3K27me3 ChIP-seq to analyze how chromatin modifications control gene expression in a specific type of CNS neuron, the mouse cerebellar granule cell (GC). We find that in proliferating GC progenitors (GCPs), H3K4me3/H3K27me3 bivalency is common at neuronal genes and undergoes dynamic changes that correlate with gene expression during migration and circuit formation. Expressing a fluorescent sensor for bivalent H3K4me3 and H3K27me3 domains revealed subnuclear bivalent foci in proliferating GCPs. Inhibiting H3K27 methyltransferases EZH1 and EZH2 in vitro and in organotypic cerebellar slices dramatically altered the expression of bivalent genes and induced the downregulation of migration-related genes and upregulation of synaptic genes, inhibited glial-guided migration, and accelerated terminal differentiation. Thus, histone bivalency is required to regulate the timing of the progression from progenitor cells to mature neurons.

EasyAmplicon: An easy-to-use, open-source, reproducible, and community-based pipeline for amplicon data analysis in microbiome research

It is difficult for beginners to learn and use amplicon analysis software because there are so many software tools to choose from, and all of them need multiple steps of operation. Herein, we provide a cross-platform, open-source, and community-supported analysis pipeline EasyAmplicon. EasyAmplicon has most of the modules needed for an amplicon analysis, including data quality control, merging of paired-end reads, dereplication, clustering or denoising, chimera detection, generation of feature tables, taxonomic diversity analysis, compositional analysis, biomarker discovery, and publication-quality visualization. EasyAmplicon includes more than 30 cross-platform modules and R packages commonly used in the field. All steps of the pipeline are integrated into RStudio, which reduces learning costs, keeps the flexibility of the analysis process, and facilitates personalized analysis. The pipeline is maintained and updated by the authors and editors of WeChat official account "Meta-genome." Our team will regularly release the latest tutorials both in Chinese and English, read the feedback from users, and provide help to them in the WeChat account and GitHub. The pipeline can be deployed on various platforms, and the installation time is less than half an hour. On an ordinary laptop, the whole analysis process for dozens of samples can be completed within 3 h. The pipeline is available at GitHub (https://github.com/YongxinLiu/EasyAmplicon) and Gitee (https://gitee.com/YongxinLiu/EasyAmplicon).

Acute stress response on Atlantic salmon: a time-course study of the effects on plasma metabolites, mucus cortisol levels, and head kidney transcriptome profile

Farmed Atlantic salmon (Salmo salar) welfare and performance can be strongly influenced by stress episodes caused by handling during farming practices. To better understand the changes occurring after an acute stress response, we exposed a group of Atlantic salmon parr to an acute stressor, which involved netting and transferring fish to several new holding tanks. We describe a time-course response to stress by sampling parr in groups before (T0) and 10, 20, 30, 45, 60, 120, 240, 300, and 330 min post-stress. A subgroup of fish was also subjected to the same stressor for a second time to assess their capacity to respond to the same challenge again within a short timeframe (ReStressed). Fish plasma was assessed for adrenocorticotropic hormone (ACTH), cortisol, and ions levels. Mucus cortisol levels were analyzed and compared with the plasma cortisol levels. At 5 selected time points (T0, 60, 90, 120, 240, and ReStressed), we compared the head kidney transcriptome profile of 10 fish per time point. The considerably delayed increase of ACTH in the plasma (60 min post-stress), and the earlier rise of cortisol levels (10 min post-stress), suggests that cortisol release could be triggered by more rapidly responding factors, such as the sympathetic system. This hypothesis may be supported by a high upregulation of several genes involved in synaptic triggering, observed both during the first and the second stress episodes. Furthermore, while the transcriptome profile showed few changes at 60 min post-stress, expression of genes in several immune-related pathways increased markedly with each successive time point, demonstrating the role of the immune system in fish coping capacity. Although many of the genes discussed in this paper are still poorly characterized, this study provides new insights regarding the mechanisms occurring during the stress response of salmon parr and may form the basis for a useful guideline on timing of sampling protocols.

Full-scale activated sludge transplantation reveals a highly resilient community structure

Well-functioning and stable microbial communities are critical for the operation of activated sludge (AS) wastewater treatment plants (WWTPs). Bioaugmentation represents a potentially useful approach to recover deteriorated systems or to support specific AS processes, but its application in full-scale WWTPs is generally problematic. We conducted a massive transplantation (in one day) exchanging AS from a donor to a recipient full-scale WWTP with similar process type (biological removal of nitrogen and phosphorus) and performance, but with differences in microbial community structure. The treatment performance in the recipient plant was not compromised and the effluent quality remained stable. The AS community structure of the recipient plant was initially very similar to the donor AS, but it almost completely restored the pre-transplantation structure approximately 40 days after transplantation, corresponding to 3 times the solid retention time. Most of the unique species of donor AS added to recipient AS disappeared quickly, although some disappeared more slowly the following months, indicating some survival and potentially a time limited function in the recipient plant. Moreover, the addition in higher abundance of most species already present in the recipient AS (e.g., the polyphosphate accumulating organisms) or the reduction of the abundance of unwanted bacteria (e.g., filamentous bacteria) in the recipient plant was not successful. Moreover, we observed similar abundance patterns after transplantation for species belonging to different functional guilds, so we did not observe an increase of the functional redundancy. Investigations of the microbial community structure in influent wastewater revealed that for some species the abundance trends in the recipient plant were closely correlated to their abundance in the influent. We showed that a very resilient microbial community was responsible for the outcome of the transplantation of AS at full-scale WWTP, potentially as a consequence of mass-immigration from influent wastewater. The overall results imply that massive transplantation of AS across different WWTPs is not a promising strategy to permanently solve operational problems. However, by choosing a compatible AS donor, short term mitigation of serious operational problems may be possible.

Uncovering the molecular mechanisms between heart failure and end-stage renal disease via a bioinformatics study

Background: Heart failure (HF) is not only a common complication in patients with end-stage renal disease (ESRD) but also a major cause of death. Although clinical studies have shown that there is a close relationship between them, the mechanism of its occurrence is unclear. The aim of this study is to explore the molecular mechanisms between HF and ESRD through comprehensive bioinformatics analysis, providing a new perspective on the crosstalk between these two diseases. Methods: The HF and ESRD datasets were downloaded from the Gene Expression Omnibus (GEO) database; we identified and analyzed common differentially expressed genes (DEGs). First, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene set variation analyses (GSVA) were applied to explore the potential biological functions and construct protein-protein interaction (PPI) networks. Also, four algorithms, namely, random forest (RF), Boruta algorithm, logical regression of the selection operator (LASSO), and support vector machine-recursive feature elimination (SVM-RFE), were used to identify the candidate genes. Subsequently, the diagnostic efficacy of hub genes for HF and ESRD was evaluated using eXtreme Gradient Boosting (XGBoost) algorithm. CIBERSORT was used to analyze the infiltration of immune cells. Thereafter, we predicted target microRNAs (miRNAs) using databases (miRTarBase, TarBase, and ENOCRI), and transcription factors (TFs) were identified using the ChEA3 database. Cytoscape software was applied to construct mRNA-miRNA-TF regulatory networks. Finally, the Drug Signatures Database (DSigDB) was used to identify potential drug candidates. Results: A total of 68 common DEGs were identified. The enrichment analysis results suggest that immune response and inflammatory factors may be common features of the pathophysiology of HF and ESRD. A total of four hub genes (BCL6, CCL5, CNN1, and PCNT) were validated using RF, LASSO, Boruta, and SVM-RFE algorithms. Their AUC values were all greater than 0.8. Immune infiltration analysis showed that immune cells such as macrophages, neutrophils, and NK cells were altered in HF myocardial tissue, while neutrophils were significantly correlated with all four hub genes. Finally, 11 target miRNAs and 10 TFs were obtained, and miRNA-mRNA-TF regulatory network construction was performed. In addition, 10 gene-targeted drugs were discovered. Conclusion: Our study revealed important crosstalk between HF and ESRD. These common pathways and pivotal genes may provide new ideas for further clinical treatment and experimental studies.

Soil Microbial Community Responses to Different Management Strategies in Almond Crop

A comparative study of organic and conventional farming systems was conducted in almond orchards to determine the effect of management practices on their fungal and bacterial communities. Soils from two orchards under organic (OM) and conventional (CM), and nearby nonmanaged (NM) soil were analyzed and compared. Several biochemical and biological parameters were measured (soil pH, electrical conductivity, total nitrogen, organic material, total phosphorous, total DNA, and fungal and bacterial DNA copies). Massive parallel sequencing of regions from fungal ITS rRNA and bacterial 16 S genes was carried out to characterize their diversity in the soil. We report a larger abundance of bacteria and fungi in soils under OM, with a more balanced fungi:bacteria ratio, compared to bacteria-skewed proportions under CM and NM. The fungal phylum Ascomycota corresponded to around the 75% relative abundance in the soil, whereas for bacteria, the phyla Proteobacteria, Acidobacteriota and Bacteroidota integrated around 50% of their diversity. Alpha diversity was similar across practices, but beta diversity was highly clustered by soil management. Linear discriminant analysis effect size (LEfSE) identified bacterial and fungal taxa associated with each type of soil management. Analyses of fungal functional guilds revealed 3-4 times larger abundance of pathogenic fungi under CM compared to OM and NM treatments. Among them, the genus Cylindrocarpon was more abundant under CM, and Fusarium under OM.

Proteomics of Retinal Extracellular Vesicles: A Review into an Unexplored Mechanism in Retinal Health and AMD Pathogenesis

Extracellular vesicles (EV) are nanosized delivery vehicles that participate in cell-to-cell communication through the selective transfer of molecular materials including RNA, DNA, lipids, and proteins. In the retina, the role of EV proteins is largely unclear, in part due to the lack of studies and the depth of proteomic analyses of EV cargo. This review summarizes the existing knowledge on retinal EV proteins and provides a comparative reanalysis of existing retinal EV proteomic datasets. Collective findings highlight that in homeostasis, the protein components of neural retinal and RPE-derived EV largely reflect the function of the host cells, while in disease RPE-EV protein composition becomes altered, favoring inflammatory modulation and potentially contributing to drusen formation. While these studies shed light on the potential roles of EV proteins in the neural retina and RPE, it is clear that comprehensive proteomic and molecular studies are required, in particular using in vivo models of retinal degenerations.

Strong restructuration of skin microbiota during captivity challenges ex-situ conservation of amphibians

In response to the current worldwide amphibian extinction crisis, conservation instances have encouraged the establishment of ex-situ collections for endangered species. The resulting assurance populations are managed under strict biosecure protocols, often involving artificial cycles of temperature and humidity to induce active and overwintering phases, which likely affect the bacterial symbionts living on the amphibian skin. However, the skin microbiota is an important first line of defense against pathogens that can cause amphibian declines, such as the chytrid Batrachochytrium dendrobatidis (Bd). Determining whether current husbandry practices for assurance populations might deplete amphibians from their symbionts is therefore essential to conservation success. Here, we characterize the effect of the transitions from the wild to captivity, and between aquatic and overwintering phases, on the skin microbiota of two newt species. While our results confirm differential selectivity of skin microbiota between species, they underscore that captivity and phase-shifts similarly affect their community structure. More specifically, the translocation ex-situ is associated with rapid impoverishment, decrease in alpha diversity and strong species turnover of bacterial communities. Shifts between active and overwintering phases also cause changes in the diversity and composition of the microbiota, and on the prevalence of Bd-inhibitory phylotypes. Altogether, our results suggest that current husbandry practices strongly restructure the amphibian skin microbiota. Although it remains to be determined whether these changes are reversible or have deleterious effects on their hosts, we discuss methods to limit microbial diversity loss ex-situ and emphasize the importance of integrating bacterial communities to applied amphibian conservation.

Maggot extracts chemo-prevent inflammation and tumorigenesis accompanied by changes in the intestinal microbiome and metabolome in AOM/DSS-induced mice

Inflammatory responses and intestinal microbiome play a crucial role in the progression of colitis-associated carcinoma (CAC). The traditional Chinese medicine maggot has been widely known owing to its clinical application and anti-inflammatory function. In this study, we investigated the preventive effects of maggot extract (ME) by intragastric administration prior to azoxymethane (AOM) and dextran sulfate sodium (DSS)-induced CAC in mice. The results showed that ME had superior advantages in ameliorating disease activity index score and inflammatory phenotype, in comparison with the AOM/DSS group. The number and size of polypoid colonic tumors were decreased after pre-administration of ME. In addition, ME was found to reverse the downregulation of tight junction proteins (zonula occluden-1 and occluding) while suppressing the levels of inflammatory factors (IL-1β and IL-6) in models. Moreover, Toll-like receptor 4 (TLR4) mediated intracellular nuclear factor-κB (NF-κB)-containing signaling cascades, including inducible nitric oxide synthase and cyclooxygenase-2, and exhibited decreasing expression in the mice model after ME pre-administration. 16s rRNA analysis and untargeted-metabolomics profiling of fecal samples inferred that ME revealed ideal prevention of intestinal dysbiosis in CAC mice, accompanied by and correlated with alterations in the composition of metabolites. Overall, ME pre-administration might be a chemo-preventive candidate in the initiation and development of CAC.

A novel approach for a joint analysis of isomiR and mRNA expression data reveals features of isomiR targeting in breast cancer

A widely used procedure for selecting significant miRNA-mRNA or isomiR-mRNA pairs out of predicted interactions involves calculating the correlation between expression levels of miRNAs/isomiRs and mRNAs in a series of samples. In this manuscript, we aimed to assess the validity of this procedure by comparing isomiR-mRNA correlation profiles in sets of sequence-based predicted target mRNAs and non-target mRNAs (negative controls). Target prediction was carried out using RNA22 and TargetScan algorithms. Spearman's correlation analysis was conducted using miRNA and mRNA sequencing data of The Cancer Genome Atlas Breast Invasive Carcinoma (TCGA-BRCA) project. Luminal A, luminal B, basal-like breast cancer subtypes, and adjacent normal tissue samples were analyzed separately. Using the sets of putative targets and non-targets, we introduced adjusted isomiR targeting activity (ITA)-the number of negatively correlated potential isomiR targets adjusted by the background (estimated using non-target mRNAs). We found that for most isomiRs a significant negative correlation between isomiR-mRNA expression levels appeared more often in a set of predicted targets compared to the non-targets. This trend was detected for both classical seed region binding types (8mer, 7mer-m8, 7mer-A1, 6mer) predicted by TargetScan and the non-classical ones (G:U wobbles and up to one mismatch or unpaired nucleotide within seed sequence) predicted by RNA22. Adjusted ITA distributions were similar for target sites located in 3'-UTRs and coding mRNA sequences, while 5'-UTRs had much lower scores. Finally, we observed strong cancer subtype-specific patterns of isomiR activity, highlighting the differences between breast cancer molecular subtypes and normal tissues. Surprisingly, our target prediction- and correlation-based estimates of isomiR activities were practically non-correlated with the average isomiR expression levels neither in cancerous nor in normal samples.

Age matters: Microbiome depletion prior to repeat mild traumatic brain injury differentially alters microbial composition and function in adolescent and adult rats

Dysregulation of the gut microbiome has been shown to perpetuate neuroinflammation, alter intestinal permeability, and modify repetitive mild traumatic brain injury (RmTBI)-induced deficits. However, there have been no investigations regarding the comparative effects that the microbiome may have on RmTBI in adolescents and adults. Therefore, we examined the influence of microbiome depletion prior to RmTBI on microbial composition and metabolome, in adolescent and adult Sprague Dawley rats. Rats were randomly assigned to standard or antibiotic drinking water for 14 days, and to subsequent sham or RmTBIs. The gut microbiome composition and metabolome were analysed at baseline, 1 day after the first mTBI, and at euthanasia (11 days following the third mTBI). At euthanasia, intestinal samples were also collected to quantify tight junction protein (TJP1 and occludin) expression. Adolescents were significantly more susceptible to microbiome depletion via antibiotic administration which increased pro-inflammatory composition and metabolites. Furthermore, RmTBI induced a transient increase in 'beneficial bacteria' (Lachnospiraceae and Faecalibaculum) in only adolescents that may indicate compensatory action in response to the injury. Finally, microbiome depletion prior to RmTBI generated a microbiome composition and metabolome that exemplified a potentially chronic pathogenic and inflammatory state as demonstrated by increased Clostridium innocuum and Erysipelatoclostridium and reductions in Bacteroides and Clostridium Sensu Stricto. Results highlight that adolescents are more vulnerable to RmTBI compared to adults and dysbiosis prior to injury may exacerbate secondary inflammatory cascades.

Deoxygenation lowers the thermal threshold of coral bleaching

Exposure to deoxygenation from climate warming and pollution is emerging as a contributing factor of coral bleaching and mortality. However, the combined effects of heating and deoxygenation on bleaching susceptibility remain unknown. Here, we employed short-term thermal stress assays to show that deoxygenated seawater can lower the thermal limit of an Acropora coral by as much as 1 °C or 0.4 °C based on bleaching index scores or dark-acclimated photosynthetic efficiencies, respectively. Using RNA-Seq, we show similar stress responses to heat with and without deoxygenated seawater, both activating putative key genes of the hypoxia-inducible factor response system indicative of cellular hypoxia. We also detect distinct deoxygenation responses, including a disruption of O2-dependent photo-reception/-protection, redox status, and activation of an immune response prior to the onset of bleaching. Thus, corals are even more vulnerable when faced with heat stress in deoxygenated waters. This highlights the need to integrate dissolved O2 measurements into global monitoring programs of coral reefs.

The association of obesity-related traits on COVID-19 severity and hospitalization is affected by socio-economic status: a multivariable Mendelian randomization study

BACKGROUND

Due to its large impact on human health, socio-economic status (SES) could at least partially influence the established association between obesity and coronavirus disease 2019 (COVID-19) severity. To estimate the independent effect of body size and SES on the clinical manifestations of COVID-19, we conducted a Mendelian randomization (MR) study.

METHODS

Applying two-sample MR approaches, we evaluated the effects of body mass index (BMI, n = 322 154), waist circumference (WC, n = 234 069), hip circumference (n = 213 019) and waist-hip ratio (n = 210 088) with respect to three COVID-19 outcomes: severe respiratory COVID-19 (cases = 8779, controls = 1 000 875), hospitalized COVID-19 (cases = 17 992, controls = 1 810 493) and COVID-19 infection (cases = 87 870, controls = 2 210 804). Applying a multivariable MR (MVMR) approach, we estimated the effect of these anthropometric traits on COVID-19 outcomes accounting for the effect of SES assessed as household income (n = 286 301).

RESULTS

BMI and WC were associated with severe respiratory COVID-19 [BMI: odds ratio (OR) = 1.51, CI = 1.24-1.84, P = 3.01e-05; WC: OR = 1.48, 95% CI = 1.15-1.91, P = 0.0019] and hospitalized COVID-19 (BMI: OR = 1.50, 95% CI = 1.32-1.72, P = 8.83e-10; WC: OR = 1.41, 95% CI = 1.20-1.67, P = 3.72e-05). Conversely, income was associated with lower odds of severe respiratory (OR = 0.70, 95% CI = 0.53-0.93, P = 0.015) and hospitalized COVID-19 (OR = 0.78, 95% CI = 0.66-0.92, P = 0.003). MVMR analyses showed that the effect of these obesity-related traits on increasing the odds of COVID-19 negative outcomes becomes null when accounting for income. Conversely, the association of income with lower odds of COVID-19 negative outcomes is not affected when including the anthropometric traits in the multivariable model.

CONCLUSION

Our findings indicate that SES contributes to the effect of obesity-related traits on COVID-19 severity and hospitalization.

H3K18 lactylation marks tissue-specific active enhancers

Background

Histone lactylation has been recently described as a novel histone post-translational modification linking cellular metabolism to epigenetic regulation.

Results

Given the expected relevance of this modification and current limited knowledge of its function, we generate genome-wide datasets of H3K18la distribution in various in vitro and in vivo samples, including mouse embryonic stem cells, macrophages, adipocytes, and mouse and human skeletal muscle. We compare them to profiles of well-established histone modifications and gene expression patterns. Supervised and unsupervised bioinformatics analysis shows that global H3K18la distribution resembles H3K27ac, although we also find notable differences. H3K18la marks active CpG island-containing promoters of highly expressed genes across most tissues assessed, including many housekeeping genes, and positively correlates with H3K27ac and H3K4me3 as well as with gene expression. In addition, H3K18la is enriched at active enhancers that lie in proximity to genes that are functionally important for the respective tissue.

Conclusions

Overall, our data suggests that H3K18la is not only a marker for active promoters, but also a mark of tissue specific active enhancers.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13059-022-02775-y.

Biomarker screening in preeclampsia: an RNA-sequencing approach based on data from multiple studies

OBJECTIVE

Biomarkers have become important in the prognosis and diagnosis of various diseases. High-throughput methods, such as RNA sequencing facilitate the detection of differentially expressed genes (DEGs), hence potential biomarker candidates. Individual studies suggest long lists of DEGs, hampering the identification of clinically relevant ones. Concerning preeclampsia - a major obstetric burden with high risk for adverse maternal and/or neonatal outcomes - limitations in diagnosis and prediction are still important issues. We, therefore, developed a workflow to facilitate the screening for biomarkers.

METHODS

On the basis of the tool DESeq2, a comprehensive workflow for identifying DEGs was established, analyzing data from several publicly available RNA-sequencing studies. We applied it to four RNA-sequencing datasets (one blood, three placenta) analyzing patients with preeclampsia and normotensive controls. We compared our results with other published approaches and evaluated their performance.

RESULTS

We identified 110 genes that are dysregulated in preeclampsia, observed in at least three of the studies analyzed, six even in all four studies. These included FLT-1, TREM-1, and FN1, which either represent established biomarkers at protein level, or promising candidates based on recent studies. For comparison, using a published meta-analysis approach, 5240 DEGs were obtained.

CONCLUSION

This study presents a data analysis workflow for preeclampsia biomarker screening, capable of identifying promising biomarker candidates, while drastically reducing the numbers of candidates. Moreover, we were also able to confirm its performance for heart failure. This approach can be applied to additional diseases for biomarker identification, and the set of DEGs identified in preeclampsia represents a resource for further studies.

Exploring Epigenomic Datasets by ChIPseeker

In many aspects of life, epigenetics, or the altering of phenotype without changes in sequences, play an essential role in biological function. A vast number of epigenomic datasets are emerging as a result of the advent of next-generation sequencing. Annotation, comparison, visualization, and interpretation of epigenomic datasets remain key aspects of computational biology. ChIPseeker is a Bioconductor package for performing these analyses among variable epigenomic datasets. The fundamental functions of ChIPseeker, including data preparation, annotation, comparison, and visualization, are explained in this article. ChIPseeker is a freely available open-source package that may be found at https://www.bioconductor.org/packages/ChIPseeker. © 2022 Wiley Periodicals LLC. Basic Protocol 1: ChIPseeker and epigenomic dataset preparation Basic Protocol 2: Annotation of epigenomic datasets Basic Protocol 3: Comparison of epigenomic datasets Basic Protocol 4: Visualization of annotated results Basic Protocol 5: Functional analysis of epigenomic datasets Basic Protocol 6: Genome-wide and locus-specific distribution of epigenomic datasets Basic Protocol 7: Heatmaps and metaplots of epigenomic datasets.

CDC20 May Serve as a Potential Biomarker-Based Risk Score System in Predicting the Prognosis of Patients with Hepatocellular Carcinoma

Background

The specificity and sensitivity of hepatocellular carcinoma (HCC) diagnostic markers are limited, hindering the early diagnosis and treatment of HCC patients. Therefore, improving prognostic biomarkers for patients with HCC is urgently needed.

Methods

HCC-related datasets were downloaded from the public databases. Differentially expressed genes (DEGs) between HCC and adjacent nontumor liver tissues were then identified. Moreover, the intersection of DEGs in four datasets (GSE138178, GSE77509, GSE84006, and TCGA) was used in the functional enrichment, and module genes were obtained by a coexpression network. Cox and Kaplan-Meier analyses were used to identify overall survival- (OS-) related genes from module genes. Area under the curve (AUC) > 0.9 of OS-related genes was then carried out in order to perform the protein-protein interaction network. The feature genes were identified by least absolute shrinkage and selection operator (LASSO). Furthermore, the hub gene was identified through the univariate Cox model, after which the correlation analysis between the hub gene and pathways was explored. Finally, infiltration in immune cell types in HCC was analyzed.

Results

A total of 2,227 upregulated genes and 1,501 downregulated DEGs were obtained in all four datasets, which were mainly found to be involved in the cell cycle and retinol metabolism. Accordingly, 998 OS-related genes were screened to construct the LASSO model. Finally, 8 feature genes (BUB1, CCNB1, CCNB2, CCNA2, AURKB, CDC20, OIP5, and TTK) were obtained. CDC20 was shown to serve as a poor prognostic gene in HCC and was mainly involved in the cell cycle. Moreover, a positive correlation was noted between the high degree of infiltration with Th2 and CDC20.

Conclusion

High expression of CDC20 predicted poor survival, as potential target in the treatment for HCC.

Nicotinamide adenine dinucleotide supplementation drives gut microbiota variation in Alzheimer’s mouse model

Alzheimer’s disease (AD) is the most common neurodegenerative disease. Growing evidence suggests an important role for gut dysbiosis and gut microbiota-host interactions in aging and neurodegeneration. Our previous works have demonstrated that supplementation with the nicotinamide adenine dinucleotide (NAD⁺) precursor, nicotinamide riboside (NR), reduced the brain features of AD, including neuroinflammation, deoxyribonucleic acid (DNA) damage, synaptic dysfunction, and cognitive impairment. However, the impact of NR administration on the intestinal microbiota of AD remains unknown. In this study, we investigated the relationship between gut microbiota and NR treatment in APP/PS1 transgenic (AD) mice. Compared with wild type (WT) mice, the gut microbiota diversity in AD mice was lower and the microbiota composition and enterotype were significantly different. Moreover, there were gender differences in gut microbiome between female and male AD mice. After supplementation with NR for 8 weeks, the decreased diversity and perturbated microbial compositions were normalized in AD mice. This included the species Oscillospira, Butyricicoccus, Desulfovibrio, Bifidobacterium, Olsenella, Adlercreutzia, Bacteroides, Akkermansia, and Lactobacillus. Our results indicate an interplay between NR and host-microbiota in APP/PS1 mice, suggesting that the effect of NR on gut dysbiosis may be an important component in its therapeutic functions in AD.

Screening seven hub genes associated with prognosis and immune infiltration in glioblastoma

Glioblastoma (GBM) is the most common and deadly primary brain tumor in adults. Diagnostic and therapeutic challenges have been raised because of poor prognosis. Gene expression profiles of GBM and normal brain tissue samples from GSE68848, GSE16011, GSE7696, and The Cancer Genome Atlas (TCGA) were downloaded. We identified differentially expressed genes (DEGs) by differential expression analysis and obtained 3,800 intersected DEGs from all datasets. Enrichment analysis revealed that the intersected DEGs were involved in the MAPK and cAMP signaling pathways. We identified seven different modules and 2,856 module genes based on the co-expression analysis. Module genes were used to perform Cox and Kaplan-Meier analysis in TCGA to obtain 91 prognosis-related genes. Subsequently, we constructed a random survival forest model and a multivariate Cox model to identify seven hub genes (KDELR2, DLEU1, PTPRN, SRBD1, CRNDE, HPCAL1, and POLR1E). The seven hub genes were subjected to the risk score and survival analyses. Among these, CRNDE may be a key gene in GBM. A network of prognosis-related genes and the top three differentially expressed microRNAs with the largest fold-change was constructed. Moreover, we found a high infiltration of plasmacytoid dendritic cells and T helper 17 cells in GBM. In conclusion, the seven hub genes were speculated to be potential prognostic biomarkers for guiding immunotherapy and may have significant implications for the diagnosis and treatment of GBM.

Staphylococcus aureus induces a muted host response in human blood that blunts the recruitment of neutrophils

Staphylococcus aureus is an opportunistic pathogen and chief among bloodstream-infecting bacteria. S. aureus produces an array of human-specific virulence factors that may contribute to immune suppression. Here, we defined the response of primary human phagocytes following infection with S. aureus using RNA-sequencing (RNA-Seq). We found that the overall transcriptional response to S. aureus was weak both in the number of genes and in the magnitude of response. Using an ex vivo bacteremia model with fresh human blood, we uncovered that infection with S. aureus resulted in the down-regulation of genes related to innate immune response and cytokine and chemokine signaling. This muted transcriptional response was conserved across diverse S. aureus clones but absent in blood exposed to heat-killed S. aureus or blood infected with the less virulent staphylococcal species Staphylococcus epidermidis. Notably, this signature was also present in patients with S. aureus bacteremia. We identified the master regulator S. aureus exoprotein expression (SaeRS) and the SaeRS-regulated pore-forming toxins as key mediators of the transcriptional suppression. The S. aureus-mediated suppression of chemokine and cytokine transcription was reflected by circulating protein levels in the plasma. Wild-type S. aureus elicited a soluble milieu that was restrictive in the recruitment of human neutrophils compared with strains lacking saeRS. Thus, S. aureus blunts the inflammatory response resulting in impaired neutrophil recruitment, which could promote the survival of the pathogen during invasive infection.

Multi-omics profiling of collagen-induced arthritis mouse model reveals early metabolic dysregulation via SIRT1 axis

Rheumatoid arthritis (RA) is characterized by joint infiltration of immune cells and synovial inflammation which leads to progressive disability. Current treatments improve the disease outcome, but the unmet medical need is still high. New discoveries over the last decade have revealed the major impact of cellular metabolism on immune cell functions. So far, a comprehensive understanding of metabolic changes during disease development, especially in the diseased microenvironment, is still limited. Therefore, we studied the longitudinal metabolic changes during the development of murine arthritis by integrating metabolomics and transcriptomics data. We identified an early change in macrophage pathways which was accompanied by oxidative stress, a drop in NAD+ level and induction of glucose transporters. We discovered inhibition of SIRT1, a NAD-dependent histone deacetylase and confirmed its dysregulation in human macrophages and synovial tissues of RA patients. Mining this database should enable the discovery of novel metabolic targets and therapy opportunities in RA.

Construction of miRNA-lncRNA-mRNA co-expression network affecting EMT-mediated cisplatin resistance in ovarian cancer

Platinum resistance is one of the major concerns in ovarian cancer treatment. Recent evidence shows the critical role of epithelial-mesenchymal transition (EMT) in this resistance. Epithelial-like ovarian cancer cells show decreased sensitivity to cisplatin after cisplatin treatment. Our study prospected the association between epithelial phenotype and response to cisplatin in ovarian cancer. Microarray dataset GSE47856 was acquired from the GEO database. After identifying differentially expressed genes (DEGs) between epithelial-like and mesenchymal-like cells, the module identification analysis was performed using weighted gene co-expression network analysis (WGCNA). The gene ontology (GO) and pathway analyses of the most considerable modules were performed. The protein-protein interaction network was also constructed. The hub genes were specified using Cytoscape plugins MCODE and cytoHubba, followed by the survival analysis and data validation. Finally, the co-expression of miRNA-lncRNA-TF with the hub genes was reconstructed. The co-expression network analysis suggests 20 modules relating to the Epithelial phenotype. The antiquewhite4, brown and darkmagenta modules are the most significant non-preserved modules in the Epithelial phenotype and contain the most differentially expressed genes. GO, and KEGG pathway enrichment analyses on these modules divulge that these genes were primarily enriched in the focal adhesion, DNA replication pathways and stress response processes. ROC curve and overall survival rate analysis show that the co-expression pattern of the brown module's hub genes could be a potential prognostic biomarker for ovarian cancer cisplatin resistance.

Identification of critical genes and molecular pathways in COVID-19 myocarditis and constructing gene regulatory networks by bioinformatic analysis

BACKGROUND

There is growing evidence of a strong relationship between COVID-19 and myocarditis. However, there are few bioinformatics-based analyses of critical genes and the mechanisms related to COVID-19 Myocarditis. This study aimed to identify critical genes related to COVID-19 Myocarditis by bioinformatic methods, explore the biological mechanisms and gene regulatory networks, and probe related drugs.

METHODS

The gene expression data of GSE150392 and GSE167028 were obtained from the Gene Expression Omnibus (GEO), including cardiomyocytes derived from human induced pluripotent stem cells infected with SARS-CoV-2 in vitro and GSE150392 from patients with myocarditis infected with SARS-CoV-2 and the GSE167028 gene expression dataset. Differentially expressed genes (DEGs) (adjusted P-Value <0.01 and |Log2 Fold Change| ≥2) in GSE150392 were assessed by NetworkAnalyst 3.0. Meanwhile, significant modular genes in GSE167028 were identified by weighted gene correlation network analysis (WGCNA) and overlapped with DEGs to obtain common genes. Functional enrichment analyses were performed by using the "clusterProfiler" package in the R software, and protein-protein interaction (PPI) networks were constructed on the STRING website (https://cn.string-db.org/). Critical genes were identified by the CytoHubba plugin of Cytoscape by 5 algorithms. Transcription factor-gene (TF-gene) and Transcription factor-microRibonucleic acid (TF-miRNA) coregulatory networks construction were performed by NetworkAnalyst 3.0 and displayed in Cytoscape. Finally, Drug Signatures Database (DSigDB) was used to probe drugs associated with COVID-19 Myocarditis.

RESULTS

Totally 850 DEGs (including 449 up-regulated and 401 down-regulated genes) and 159 significant genes in turquoise modules were identified from GSE150392 and GSE167028, respectively. Functional enrichment analysis indicated that common genes were mainly enriched in biological processes such as cell cycle and ubiquitin-protein hydrolysis. 6 genes (CDK1, KIF20A, PBK, KIF2C, CDC20, UBE2C) were identified as critical genes. TF-gene interactions and TF-miRNA coregulatory network were constructed successfully. A total of 10 drugs, (such as Etoposide, Methotrexate, Troglitazone, etc) were considered as target drugs for COVID-19 Myocarditis.

CONCLUSIONS

Through bioinformatics method analysis, this study provides a new perspective to explore the pathogenesis, gene regulatory networks and provide drug compounds as a reference for COVID-19 Myocarditis. It is worth highlighting that critical genes (CDK1, KIF20A, PBK, KIF2C, CDC20, UBE2C) may be potential biomarkers and treatment targets of COVID-19 Myocarditis for future study.

Proteomics Reveals Long-Term Alterations in Signaling and Metabolic Pathways Following Both Myocardial Infarction and Chemically Induced Denervation

Myocardial infraction (MI) is the principal risk factor for the onset of heart failure (HF). Investigations regarding the physiopathology of MI progression to HF have revealed the concerted engagement of other tissues, such as the autonomic nervous system and the medulla oblongata (MO), giving rise to systemic effects, important in the regulation of heart function. Cardiac sympathetic afferent denervation following application of resiniferatoxin (RTX) attenuates cardiac remodelling and restores cardiac function following MI. While the physiological responses are well documented in numerous species, the underlying molecular responses during the initiation and progression from MI to HF remains unclear. We obtained multi-tissue time course proteomics with a murine model of HF induced by MI in conjunction with RTX application. We isolated tissue sections from the left ventricle (LV), MO, cervical spinal cord and cervical vagal nerves at four time points over a 12-week study. Bioinformatic analyses consistently revealed a high statistical enrichment for metabolic pathways in all tissues and treatments, implicating a central role of mitochondria in the tissue-cellular response to both MI and RTX. In fact, the additional functional pathways found to be enriched in these tissues, involving the cytoskeleton, vesicles and signal transduction, could be downstream of responses initiated by mitochondria due to changes in neuronal pulse frequency after a shock such as MI or the modification of such frequency communication from the heart to the brain after RTX application. Development of future experiments, based on our proteomic results, should enable the dissection of more precise mechanisms whereby metabolic changes in neuronal and cardiac tissues can effectively ameliorate the negative physiological effects of MI via RTX application.

Proximity-based labeling reveals DNA damage-induced phosphorylation of fused in sarcoma (FUS) causes distinct changes in the FUS protein interactome

Accumulation of cytoplasmic inclusions containing fused in sarcoma (FUS), an RNA/DNA-binding protein, is a common hallmark of frontotemporal lobar degeneration and amyotrophic lateral sclerosis neuropathology. We have previously shown that DNA damage can trigger the cytoplasmic accumulation of N-terminally phosphorylated FUS. However, the functional consequences of N-terminal FUS phosphorylation are unknown. To gain insight into this question, we utilized proximity-dependent biotin labeling via ascorbate peroxidase 2 aired with mass spectrometry to investigate whether N-terminal phosphorylation alters the FUS protein-protein interaction network (interactome), and subsequently, FUS function. We report the first analysis comparing the interactomes of three FUS variants: homeostatic wildtype FUS (FUS WT), phosphomimetic FUS (FUS PM; a proxy for N-terminally phosphorylated FUS), and the toxic FUS proline 525 to leucine mutant (FUS P525L) that causes juvenile amyotrophic lateral sclerosis. We found that the phosphomimetic FUS interactome is uniquely enriched for a group of cytoplasmic proteins that mediate mRNA metabolism and translation, as well as nuclear proteins involved in the spliceosome and DNA repair functions. Furthermore, we identified and validated the RNA-induced silencing complex RNA helicase MOV10 as a novel interacting partner of FUS. Finally, we provide functional evidence that N-terminally phosphorylated FUS may disrupt homeostatic translation and steady-state levels of specific mRNA transcripts. Taken together, these results highlight phosphorylation as a unique modulator of the interactome and function of FUS.

Integrative Proteome and Phosphoproteome Profiling of Early Cold Response in Maize Seedlings

Cold limits the growth and yield of maize in temperate regions, but the molecular mechanism of cold adaptation remains largely unexplored in maize. To identify early molecular events during cold shock, maize seedlings were treated under 4 °C for 30 min and 2 h, and analyzed at both the proteome and phosphoproteome levels. Over 8500 proteins and 19,300 phosphopeptides were quantified. About 660 and 620 proteins were cold responsive at protein abundance or site-specific phosphorylation levels, but only 65 proteins were shared between them. Functional enrichment analysis of cold-responsive proteins and phosphoproteins revealed that early cold response in maize is associated with photosynthesis light reaction, spliceosome, endocytosis, and defense response, consistent with similar studies in Arabidopsis. Thirty-two photosynthesis proteins were down-regulated at protein levels, and 48 spliceosome proteins were altered at site-specific phosphorylation levels. Thirty-one kinases and 33 transcriptional factors were cold responsive at protein, phosphopeptide, or site-specific phosphorylation levels. Our results showed that maize seedlings respond to cold shock rapidly, at both the proteome and phosphoproteome levels. This study provides a comprehensive landscape at the cold-responsive proteome and phosphoproteome in maize seedlings that can be a significant resource to understand how C₄ plants respond to a sudden temperature drop.

Bioinformatics analysis identifies diagnostic biomarkers and their correlation with immune infiltration in diabetic nephropathy

Background

Diabetic nephropathy (DN) is a major cause of end-stage renal disease (ESRD). Currently, microalbuminuria is mainly used as a diagnostic indicator of DN, but there are still limitations and lack of immune-related diagnostic markers. In this study, we aimed to explore diagnostic biomarkers associated with immune infiltration of DN.

Methods

Immune-related differentially expressed genes (DEGs) were derived from those at the intersection of the ImmPort database and DEGs identified from 3 datasets, which were based on the Gene Expression Omnibus (GEO). Functional enrichment analyses were performed; a protein-protein interaction (PPI) network was constructed; and hub genes were identified by Search Tool for the Retrieval of Interacting Genes/Proteins (STRING). After screening the key genes using least absolute shrinkage and selection operator (LASSO) and support vector machine recursive feature elimination (SVM-RFE), a prediction model for DN was constructed. The predictive performance of the model was quantified by receiver-operating characteristic curve, decision curve analysis, and nomogram. Next, infiltration of 22 types of immune cells in DN kidney tissue was evaluated using cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT). Expression of diagnostic markers was analyzed in DN and control patient groups to determine the genes with the maximum diagnostic potential. Finally, we explored the correlation between diagnostic markers and immune cells.

Results

Overall, 191 immune-related DEGs were identified, that primarily positively regulated with cell adhesion, T cell activation, leukocyte proliferation and migration, urogenital system development, lymphocyte differentiation and proliferation, and mononuclear cell proliferation. Gene sets were related to the PI3K-Akt, MAPK, Rap1, and WNT signaling pathways. Finally, CCL19, CD1C, and IL33 were identified as diagnostic markers of DN and recognized in the 3 datasets [area under the curve (AUC) =0.921]. Immune cell infiltration analysis demonstrated that CCL19 was positively correlated with macrophages M1 (R=0.47, P<0.001) and macrophages M2 (R=0.75, P<0.001). CD1C was positively correlated with macrophages M1 (R=0.47, P<0.05), macrophages M2 (R=0.75, P<0.01), and monocytes (R=0.42, P<0.01). IL33 was positively correlated with macrophages M1 (R=0.45, P<0.05), macrophages M2 (R=0.74, P<0.01), and monocytes (R=0.41, P<0.01).

Conclusions

Our results provide evidence that CCL19, CD1C, and IL33, which are associated with immune infiltration, are the potential diagnostic biomarkers for DN candidates.

Zika virus impacts extracellular vesicle composition and cellular gene expression in macaque early gestation trophoblasts

Zika virus (ZIKV) infection at the maternal-placental interface is associated with adverse pregnancy outcomes including fetal demise and pregnancy loss. To determine how infection impacts placental trophoblasts, we utilized rhesus macaque trophoblast stem cells (TSC) that can be differentiated into early gestation syncytiotrophoblasts (ST) and extravillous trophoblasts (EVT). TSCs and STs, but not EVTs, were highly permissive to productive infection with ZIKV strain DAK AR 41524. The impact of ZIKV on the cellular transcriptome showed that infection of TSCs and STs increased expression of immune related genes, including those involved in type I and type III interferon responses. ZIKV exposure altered extracellular vesicle (EV) mRNA, miRNA and protein cargo, including ZIKV proteins, regardless of productive infection. These findings suggest that early gestation macaque TSCs and STs are permissive to ZIKV infection, and that EV analysis may provide a foundation for identifying non-invasive biomarkers of placental infection in a highly translational model.

Identification of Bioactive Components of Stephania epigaea Lo and Their Potential Therapeutic Targets by UPLC-MS/MS and Network Pharmacology

Stephania epigaea, an important traditional folk medicinal plant, elucidating its bioactive compound profiles and their molecular mechanisms of action on human health, would better understand its traditional therapies and guide their use in preclinical and clinical. This study aims to detect the critical therapeutic compounds, predict their targets, and explore potential therapeutic molecular mechanisms. This work first determined metabolites from roots, stems, and flowering twigs of S. epigaea by a widely targeted metabolomic analysis assay. Then, the drug likeness of the compounds and their pharmacokinetic profiles were screened by the ADMETlab server. The target proteins of active compounds were further analyzed by PPI combing with GO and KEGG cluster enrichment analysis. Finally, the interaction networks between essential compounds, targets, and disease-associated pathways were constructed, and the essential compounds binding to their possible target proteins were verified by molecular docking. Five key target proteins (EGFR, HSP90AA1, SRC, TNF, and CASP3) and twelve correlated metabolites, including aknadinine, cephakicine, homostephanoline, and N-methylliriodendronine associated with medical applications of S. epigaea, were identified, and the compounds and protein interactions were verified. The key active ingredients are mainly accumulated in the root, which indicates that the root is the main medicinal tissue. This study demonstrated that S. epigaea might exert the desired disease efficacy mainly through twelve components interacting via five essential target proteins. EGFR is the most critical one, which deserves further verification by biological studies.

Dual RNA Sequencing Reveals Key Events When Different Giardia Life Cycle Stages Interact With Human Intestinal Epithelial Cells In Vitro

Giardia intestinalis is a protozoan parasite causing diarrheal disease, giardiasis, after extracellular infection of humans and other mammals’ intestinal epithelial cells (IECs) of the upper small intestine. The parasite has two main life cycle stages: replicative trophozoites and transmissive cysts. Differentiating parasites (encysting cells) and trophozoites have recently been shown to be present in the same regions of the upper small intestine, whereas most mature cysts are found further down in the intestinal system. To learn more about host-parasite interactions during Giardia infections, we used an in vitro model of the parasite’s interaction with host IECs (differentiated Caco-2 cells) and Giardia WB trophozoites, early encysting cells (7 h), and cysts. Dual RNA sequencing (Dual RNAseq) was used to identify differentially expressed genes (DEGs) in both Giardia and the IECs, which might relate to establishing infection and disease induction. In the human cells, the largest gene expression changes were found in immune and MAPK signaling, transcriptional regulation, apoptosis, cholesterol metabolism and oxidative stress. The different life cycle stages of Giardia induced a core of similar DEGs but at different levels and there are many life cycle stage-specific DEGs. The metabolic protein PCK1, the transcription factors HES7, HEY1 and JUN, the peptide hormone CCK and the mucins MUC2 and MUC5A are up-regulated in the IECs by trophozoites but not cysts. Cysts specifically induce the chemokines CCL4L2, CCL5 and CXCL5, the signaling protein TRKA and the anti-bacterial protein WFDC12. The parasite, in turn, up-regulated a large number of hypothetical genes, high cysteine membrane proteins (HCMPs) and oxidative stress response genes. Early encysting cells have unique DEGs compared to trophozoites (e.g. several uniquely up-regulated HCMPs) and interaction of these cells with IECs affected the encystation process. Our data show that different life cycle stages of Giardia induce different gene expression responses in the host cells and that the IECs in turn differentially affect the gene expression in trophozoites and early encysting cells. This life cycle stage-specific host-parasite cross-talk is an important aspect to consider during further studies of Giardia’s molecular pathogenesis.

Microarray analysis of breast cancer gene expression profiling in response to 2-deoxyglucose, metformin, and glucose starvation

BACKGROUND

Breast cancer (BC) is the most frequently diagnosed cancer in women. Altering glucose metabolism and its effects on cancer progression and treatment resistance is an emerging interest in BC research. For instance, combining chemotherapy with glucose-lowering drugs (2-deoxyglucose (2-DG), metformin (MET)) or glucose starvation (GS) has shown better outcomes than with chemotherapy alone. However, the genes and molecular mechanisms that govern the action of these glucose deprivation conditions have not been fully elucidated. Here, we investigated the differentially expressed genes in MCF-7 and MDA-MB-231 BC cell lines upon treatment with glucose-lowering drugs (2-DG, MET) and GS using microarray analysis to study the difference in biological functions between the glucose challenges and their effect on the vulnerability of BC cells.

METHODS

MDA-MB-231 and MCF-7 cells were treated with 20 mM MET or 4 mM 2-DG for 48 h. GS was performed by gradually decreasing the glucose concentration in the culture medium to 0 g/L, in which the cells remained with fetal bovine serum for one week. Expression profiling was carried out using Affymetrix Human Clariom S microarrays. Differentially expressed genes were obtained from the Transcriptome Analysis Console and enriched using DAVID and R packages.

RESULTS

Our results showed that MDA-MB-231 cells were more responsive to glucose deprivation than MCF-7 cells. Endoplasmic reticulum stress response and cell cycle inhibition were detected after all three glucose deprivations in MDA-MB-231 cells and only under the metformin and GS conditions in MCF-7 cells. Induction of apoptosis and inhibition of DNA replication were observed with all three treatments in MDA-MB-231 cells and metformin-treated MCF-7 cells. Upregulation of cellular response to reactive oxygen species and inhibition of DNA repair mechanisms resulted after metformin and GS administration in MDA-MB-231 cell lines and metformin-treated MCF-7 cells. Autophagy was induced after 2-DG treatment in MDA-MB-231 cells and after metformin in MCF-7 cells. Finally, inhibition of DNA methylation were observed only with GS in MDA-MB-231 cells.

CONCLUSION

The procedure used to process cancer cells and analyze their expression data distinguishes our study from others. GS had the greatest effect on breast cancer cells compared to 2-DG and MET. Combining MET and GS could restrain both cell lines, making them more vulnerable to conventional chemotherapy.

Microbial biogeography of the wombat gastrointestinal tract

Most herbivorous mammals have symbiotic microbes living in their gastrointestinal tracts that help with harvesting energy from recalcitrant plant fibre. The bulk of research into these microorganisms has focused on samples collected from faeces, representing the distal region of the gastrointestinal (GI) tract. However, the GI tract in herbivorous mammals is typically long and complex, containing different regions with distinct physico-chemical properties that can structure resident microbial communities. Little work has been done to document GI microbial communities of herbivorous animals at these sites. In this study, we use 16S rRNA gene sequencing to characterize the microbial biogeography along the GI tract in two species of wombats. Specifically, we survey the microbes along four major gut regions (stomach, small intestine, proximal colon, distal colon) in a single bare-nosed wombat (Vombatus ursinus) and a single southern hairy-nosed wombat (Lasiorhinus latifrons). Our preliminary results show that GI microbial communities of wombats are structured by GI region. For both wombat individuals, we observed a trend of increasing microbial diversity from stomach to distal colon. The microbial composition in the first proximal colon region was more similar between wombat species than the corresponding distal colon region in the same species. We found several microbial genera that were differentially abundant between the first proximal colon (putative site for primary plant fermentation) and distal colon regions (which resemble faecal samples). Surprisingly, only 10.6% (98) and 18.8% (206) of amplicon sequence variants (ASVs) were shared between the first proximal colon region and the distal colon region for the bare-nosed and southern hairy-nosed wombat, respectively. These results suggest that microbial communities in the first proximal colon region-the putative site of primary plant fermentation in wombats-are distinct from the distal colon, and that faecal samples may have limitations in capturing the diversity of these communities. While faeces are still a valuable and effective means of characterising the distal colon microbiota, future work seeking to better understand how GI microbiota impact the energy economy of wombats (and potentially other hindgut-fermenting mammals) may need to take gut biogeography into account.

Analysis of colonic mucosa-associated microbiota using endoscopically collected lavage

The bacterial composition of the gut lumen and mucosa is distinct and the mucosa-associated bacteria are thought to play a more critical role in interactions with the host immune system. However, limited studies of the gut mucosal microbiota in humans have been available due to methodological challenges. Here, we evaluated the potential use of colonic lavage samples for mucosal microbiota analysis in humans. Among the different types of colonic mucosal samples collected from healthy volunteers, the lavage samples contained a higher amount of bacterial DNA and were less contaminated with host DNA compared to mucosal brushing (brush) and biopsy. Although 16S gene amplicon sequencing showed that the bacterial composition of the lavage was intermediate between that of feces and biopsy, mucosal bacteria abundant in the biopsy were also enriched in lavage samples. Furthermore, differences in mucosal microbes between non-smokers and smokers were detectable in lavage samples. Our data emphasize that colonic lavage is suitable for analysis of the mucosal microbiota. Given its minimal invasiveness and high bacterial DNA content, the colonic lavage will promote research on the human mucosal microbiota, especially in gastrointestinal disorders.

Identification of molecular signatures associated with sleep disorder and Alzheimer's disease

BACKGROUND

Alzheimer's disease (AD) and sleep disorders are both neurodegenerative conditions characterized by impaired or absent sleep. However, potential common pathogenetic mechanisms of these diseases are not well characterized.

METHODS

Differentially expressed genes (DEGs) were identified using publicly available human gene expression profiles GSE5281 for AD and GSE40562 for sleep disorder. DEGs common to the two datasets were used for enrichment analysis, and we performed multi-scale embedded gene co-expression network analysis (MEGENA) for common DEGs. Fast gene set enrichment analysis (fGSEA) was used to obtain common pathways, while gene set variation analysis (GSVA) was applied to quantify those pathways. Subsequently, we extracted the common genes between module genes identified by MEGENA and genes of the common pathways, and we constructed protein-protein interaction (PPI) networks. The top 10 genes with the highest degree of connectivity were classified as hub genes. Common genes were used to perform Metascape enrichment analysis for functional enrichment. Furthermore, we quantified infiltrating immune cells in patients with AD or sleep disorder and in controls.

RESULTS

DEGs common to the two disorders were involved in the citrate cycle and the HIF-1 signaling pathway, and several common DEGs were related to signaling pathways regulating the pluripotency of stem cells, as well as 10 other pathways. Using MEGENA, we identified 29 modules and 1,498 module genes in GSE5281, and 55 modules and 1,791 module genes in GSE40562. Hub genes involved in AD and sleep disorder were ATP5A1, ATP5B, COX5A, GAPDH, NDUFA9, NDUFS3, NDUFV2, SOD1, UQCRC1, and UQCRC2. Plasmacytoid dendritic cells and T helper 17 cells had the most extensive infiltration in both AD and sleep disorder.

CONCLUSION

AD pathology and pathways of neurodegeneration participate in processes contributing in AD and sleep disorder. Hub genes may be worth exploring as potential candidates for targeted therapy of AD and sleep disorder.

Early life skin microbial trajectory as a function of vertical and environmental transmission in Bornean foam-nesting frogs

BACKGROUND

The amphibian skin microbiome is an important mediator of host health and serves as a potential source of undiscovered scientifically significant compounds. However, the underlying modalities of how amphibian hosts obtain their initial skin-associated microbiome remains unclear. Here, we explore microbial transmission patterns in foam-nest breeding tree frogs from Southeast Asia (Genus: Polypedates) whose specialized breeding strategy allows for better delineation between vertically and environmentally derived microbes. To facilitate this, we analyzed samples associated with adult frog pairs taken after mating-including adults of each sex, their foam nests, environments, and tadpoles before and after environmental interaction-for the bacterial communities using DNA metabarcoding data (16S rRNA). Samples were collected from frogs in-situ in Brunei, Borneo, a previously unsampled region for amphibian-related microbial diversity.

RESULTS

Adult frogs differed in skin bacterial communities among species, but tadpoles did not differ among species. Foam nests had varying bacterial community composition, most notably in the nests' moist interior. Nest interior bacterial communities were discrete for each nest and overall displayed a narrower diversity compared to the nest exteriors. Tadpoles sampled directly from the foam nest displayed a bacterial composition less like the nest interior and more similar to that of the adults and nest exterior. After one week of pond water interaction the tadpole skin microbiome shifted towards the tadpole skin and pond water microbial communities being more tightly coupled than between tadpoles and the internal nest environment, but not to the extent that the skin microbiome mirrored the pond bacterial community.

CONCLUSIONS

Both vertical influence and environmental interaction play a role in shaping the tadpole cutaneous microbiome. Interestingly, the interior of the foam nest had a distinct bacterial community from the tadpoles suggesting a limited environmental effect on tadpole cutaneous bacterial selection at initial stages of life. The shift in the tadpole microbiome after environmental interaction indicates an interplay between underlying host and ecological mechanisms that drive community formation. This survey serves as a baseline for further research into the ecology of microbial transmission in aquatic animals.

Plant secondary cell wall proteome analysis with an inducible system for xylem vessel cell differentiation

Plant cell walls are typically composed of polysaccharide polymers and cell wall proteins (CWPs). CWPs account for approximately 10% of the plant cell wall structure and perform a wide range of functions. Previous studies have identified approximately 1000 CWPs in the model plant Arabidopsis thaliana; however, the analyses mainly targeted primary cell walls, which are generated at cell division. In contrast, little is known about CWPs in secondary cell walls (SCWs), which are rigid and contain the phenolic polymer lignin. Here, we performed a cell wall proteome analysis to obtain novel insights into CWPs in SCWs. To this end, we tested multiple methods for cell wall extraction with cultured Arabidopsis cells carrying the VND7-VP16-GR system, with which cells can be transdifferentiated into xylem-vessel-like cells with lignified SCWs by dexamethasone treatment. We then subjected the protein samples to in-gel trypsin digestion followed by LC-MS/MS analysis. The different extraction methods resulted in the detection of different cell wall fraction proteins (CWFPs). In particular, centrifugation conditions had a strong impact on the extracted CWFP species, resulting in the increased number of identified CWFPs. We successfully identified 896 proteins as CWFPs in total, including proteases, expansins, purple phosphatase, well-known lignin-related enzymes (laccase and peroxidase), and 683 of 896 proteins were newly identified CWFPs. These results demonstrate the usefulness of our CWP analysis method. Further analyses of SCW-related CWPs could be expected to produce information useful for understanding the roles of CWPs in plant cell functions.

Bacterial low-abundant taxa are key determinants of a healthy airway metagenome in the early years of human life

The default removal of low-abundance (rare) taxa from microbial community analyses may lead to an incomplete picture of the taxonomic and functional microbial potential within the human habitat. Publicly available shotgun metagenomics data of healthy children and children with cystic fibrosis (CF) were reanalysed to study the development of the rare species biosphere, which was here defined by either the 15th, 25th or 35th species abundance percentile. We found that healthy children contained an age-independent network of abundant (core) and rare species with both entities being essential in maintaining the network structure. The protein sequence usage for more than 100 bacterial metabolic pathways differed between the core and rare species biosphere. In CF children, the background structure was underdeveloped and random forest bootstrapping based on all constituents of the early airway metagenome and host-associated factors indicated that rare taxa were the most important variables in deciding whether a child was healthy or suffered from the life-limiting CF disease. Attempts failed to make the age-independent CF network as robust as the healthy structure when an increasing number of bacterial taxa from the healthy network was incorporated into the CF structure by computer-based model simulations. However, the transfer of a key combination of taxa from the healthy to the CF network structure with high species diversity and low species dominance, correlated with a more robust CF network and a topological approximation of CF and healthy graph structures. Rothia mucilaginosa, Streptococci and rare species were essential in improving the underdeveloped CF network.