VennPainter: A Tool for the Comparison and Identification of Candidate Genes Based on Venn Diagrams

Transcriptome Analysis Reveals the Role of Sucrose in the Production of Latilactobacillus sakei L3 Exopolysaccharide

Latilactobacillus (L.) sakei is a species of lactic acid bacteria (LAB) mostly studied according to its application in food fermentation. Previously, L. sakei L3 was isolated by our laboratory and possessed the capability of high exopolysaccharide (EPS) yield during sucrose-added fermentation. However, the understanding of sucrose promoting EPS production is still limited. Here, we analyzed the growth characteristics of L. sakei L3 and alterations of its transcriptional profiles during sucrose-added fermentation. The results showed that L. sakei L3 could survive between pH 4.0 and pH 9.0, tolerant to NaCl (<10%, w/v) and urea (<6%, w/v). Meanwhile, transcriptomic analysis showed that a total of 426 differentially expressed genes and eight non-coding RNAs were identified. Genes associated with sucrose metabolism were significantly induced, so L. sakei L3 increased the utilization of sucrose to produce EPS, while genes related to uridine monophosphate (UMP), fatty acids and folate synthetic pathways were significantly inhibited, indicating that L. sakei L3 decreased self-growth, substance and energy metabolism to satisfy EPS production. Overall, transcriptome analysis provided valuable insights into the mechanisms by which L. sakei L3 utilizes sucrose for EPS biosynthesis. The study provided a theoretical foundation for the further application of functional EPS in the food industry.

Study of selenium enrichment metabolomics in Bacillus subtilis BSN313 via transcriptome analysis

In this study, the transcriptome analysis was practiced to identify potential genes of probiotic Bacillus subtilis BSN313 involved in selenium (Se) enrichment metabolism. The transcriptomic variation of the strain was deliberated in presence of three different sodium selenite concentrations (0, 3, and 20 μg/mL). The samples were taken at 1 and 13 h subsequent to inoculation of selenite and gene expression profiles in Se metabolism were analyzed through RNA sequencing. The gene expression levels of the pre log phase were lower than the stationary phase. It is because, the bacteria has maximum grown with high concentration of Se (enriched with organic Se), at stationary phase. Bacterial culture containing 3 μg/mL concentration of inorganic Se (sodium selenite) has shown highest gene expression as compared to no or high concentration of Se. This concentration (3 μg/mL) of sodium selenite (as Se) in the medium promoted the upregulation of thioredoxin reductase expression, whereas its higher Se concentration inhibited the formation of selenomethionine (SeMet). The result of 5 L bioreactor fermentation showed that SeMet was also detected in the fermentation supernatant as the growth entered in the late stationary phase and reached up to 857.3 ng/mL. The overall intracellular SeMet enriched content in BSN313 was extended up to 23.4 μg/g dry cell weight. The other two selenoamino acids (Se-AAs), methyl-selenocysteine, and selenocysteine were hardly detected in medium supernatant. From this study, it was concluded that SeMet was the highest content of organic Se byproduct biosynthesized by B. subtilis BSN313 strain in Se-enriched medium during stationary phase. Thus, B. subtilis BSN313 can be considered a commercial probiotic strain that can be used in the food and pharmaceutical industries. This is because it can meet the commercial demand for Se-AAs (SeMet) in both industries.

Investigation of autophagy‑related genes and immune infiltration in calcific aortic valve disease: A bioinformatics analysis and experimental validation

The present study aimed to elucidate the role of autophagy-related genes (ARGs) in calcific aortic valve disease (CAVD) and their potential interactions with immune infiltration via experimental verification and bioinformatics analysis. A total of three microarray datasets (GSE12644, GSE51472 and GSE77287) were obtained from the Gene Expression Omnibus database, and gene set enrichment analysis was performed to identify the relationship between autophagy and CAVD. After differentially expressed genes and differentially expressed ARGs (DEARGs) were identified using CAVD samples and normal aortic valve samples, a functional analysis was performed, including Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses, protein-protein interaction network construction, hub gene identification and validation, immune infiltration and drug prediction. The results of the present study indicated a significant relationship between autophagy and CAVD. A total of 46 DEARGs were identified. GO and pathway enrichment analyses revealed the complex roles of DEARGs in regulating CAVD, including multiple gene functions and pathways. A total of 10 hub genes were identified, with three (SPP1, CXCL12 and CXCR4) consistently upregulated in CAVD samples compared with normal aortic valve samples in multiple datasets and experimental validation. Immune infiltration analyses demonstrated significant differences in immune cell proportions between CAVD samples and normal aortic valve samples, thus showing the crucial role of immune infiltration in CAVD development. Furthermore, therapeutic drugs were predicted that could target the identified hub genes, including bisphenol A, resveratrol, progesterone and estradiol. In summary, the present study illuminated the crucial role of autophagy in CAVD development and identified key ARGs as potential therapeutic targets. In addition, the observed immune cell infiltration and predicted autophagy-related drugs suggest promising avenues for future research and novel CAVD treatments.

Microglial Transcriptional Signatures in the Central Nervous System: Toward A Future of Unraveling Their Function in Health and Disease

Microglia, the resident immune cells of the central nervous system (CNS), are primarily derived from the embryonic yolk sac and make their way to the CNS during early development. They play key physiological and immunological roles across the life span, throughout health, injury, and disease. Recent transcriptomic studies have identified gene transcript signatures expressed by microglia that may provide the foundation for unprecedented insights into their functions. Microglial gene expression signatures can help distinguish them from macrophage cell types to a reasonable degree of certainty, depending on the context. Microglial expression patterns further suggest a heterogeneous population comprised of many states that vary according to the spatiotemporal context. Microglial diversity is most pronounced during development, when extensive CNS remodeling takes place, and following disease or injury. A next step of importance for the field will be to identify the functional roles performed by these various microglial states, with the perspective of targeting them therapeutically.

Chromosome-level genome assembly of the deep-sea snail Phymorhynchus buccinoides provides insights into the adaptation to the cold seep habitat

BACKGROUND

The deep-sea snail Phymorhynchus buccinoides belongs to the genus Phymorhynchus (Neogastropoda: Raphitomidae), and it is a dominant specie in the cold seep habitat. As the environment of the cold seep is characterized by darkness, hypoxia and high concentrations of toxic substances such as hydrogen sulfide (H2S), exploration of the diverse fauna living around cold seeps will help to uncover the adaptive mechanisms to this unique habitat. In the present study, a chromosome-level genome of P. buccinoides was constructed and a series of genomic and transcriptomic analyses were conducted to explore its molecular adaptation mechanisms to the cold seep environments.

RESULTS

The assembled genome size of the P. buccinoides was approximately 2.1 Gb, which is larger than most of the reported snail genomes, possibly due to the high proportion of repetitive elements. About 92.0% of the assembled base pairs of contigs were anchored to 34 pseudo-chromosomes with a scaffold N50 size of 60.0 Mb. Compared with relative specie in the shallow water, the glutamate regulative and related genes were expanded in P. buccinoides, which contributes to the acclimation to hypoxia and coldness. Besides, the relatively high mRNA expression levels of the olfactory/chemosensory genes in osphradium indicate that P. buccinoides might have evolved a highly developed and sensitive olfactory organ for its orientation and predation. Moreover, the genome and transcriptome analyses demonstrate that P. buccinoides has evolved a sulfite-tolerance mechanism by performing H2S detoxification. Many genes involved in H2S detoxification were highly expressed in ctenidium and hepatopancreas, suggesting that these tissues might be critical for H2S detoxification and sulfite tolerance.

CONCLUSIONS

In summary, our report of this chromosome-level deep-sea snail genome provides a comprehensive genomic basis for the understanding of the adaptation strategy of P. buccinoides to the extreme environment at the deep-sea cold seeps.

Btg1 and Btg2 regulate neonatal cardiomyocyte cell cycle arrest

Rodent cardiomyocytes undergo mitotic arrest in the first postnatal week. Here, we investigate the role of transcriptional co-regulator Btg2 (B-cell translocation gene 2) and functionally-similar homolog Btg1 in postnatal cardiomyocyte cell cycling and maturation. Btg1 and Btg2 (Btg1/2) are expressed in neonatal C57BL/6 mouse left ventricles coincident with cardiomyocyte cell cycle arrest. Btg1/2 constitutive double knockout (DKO) mouse hearts exhibit increased pHH3+ mitotic cardiomyocytes compared to Wildtype at postnatal day (P)7, but not at P30. Similarly, neonatal AAV9-mediated Btg1/2 double knockdown (DKD) mouse hearts exhibit increased EdU+ mitotic cardiomyocytes compared to Scramble AAV9-shRNA controls at P7, but not at P14. In neonatal rat ventricular myocyte (NRVM) cultures, siRNA-mediated Btg1/2 single and double knockdown cohorts showed increased EdU+ cardiomyocytes compared to Scramble siRNA controls, without increase in binucleation or nuclear DNA content. RNAseq analyses of Btg1/2-depleted NRVMs support a role for Btg1/2 in inhibiting cell proliferation, and in modulating reactive oxygen species response pathways, implicated in neonatal cardiomyocyte cell cycle arrest. Together, these data identify Btg1 and Btg2 as novel contributing factors in mammalian cardiomyocyte cell cycle arrest after birth.

Neurobiochemical, Peptidomic, and Bioinformatic Approaches to Characterize Tauopathy Peptidome Biomarker Candidates in Experimental Mouse Model of Traumatic Brain Injury

Traumatic brain injury (TBI) is a multidimensional damage, and currently, no FDA-approved medicine is available. Multiple pathways in the cell are triggered through a head injury (e.g., calpain and caspase activation), which truncate tau and generate variable fragment sizes (MW 400-45,000 K). In this study, we used an open-head TBI mouse model generated by controlled cortical impact (CCI) and collected ipsilateral (IC) and contralateral (CC) mice htau brain cortices at one (D1) three (D3), and seven (D7) days post-injury. We implemented immunological (antibody-based detection) and peptidomic approaches (nano-reversed-phase liquid chromatography/tandem mass spectrometry) to investigate proteolytic tau peptidome (low molecular weight (LMW) < 10 K)) and pathological phosphorylation sites (high-molecular-weight (HMW); > 10 K) derived from CCI-TBI animal models. Our immunoblotting analysis verified tau hyperphosphorylation, HMW, and HMW breakdown products (HMW-BDP) formation of tau (e.g., pSer₂₀₂, pThr₁₈₁, pThr₂₃₁, pSer₃₉₆, and pSer₄₀₄), following CCI-TBI. Peptidomic data revealed unique sequences of injury-dependent proteolytic peptides generated from human tau protein. Among the N-terminal tau peptides, EIPEGTTAEEAGIGDTPSLEDEAAGHVTQA (a.a. 96-125) and AQPHTEIPEGTTAEEAGIGDTPSLEDEAAGHVTQARM (a.a. 91-127). Examples of tau C-terminal peptides identified include NVSSTGSIDMVDSPQLATLADEVSASLAKQGL (a.a. 410-441) and QLATLADEVSASLAKQGL (a.a. 424-441). Our peptidomic bioinformatic tools showed the association of proteases, such as CAPN1, CAPN2, and CTSL; CASP1, MMP7, and MMP9; and ELANE, GZMA, and MEP1A, in CCI-TBI tau peptidome. In clinical trials for novel TBI treatments, it might be useful to monitor a subset of tau peptidome as targets for biomarker utility and use them for a "theranostic" approach.

Transcriptome analysis of newly established carboplatin-resistant ovarian cancer cell model reveals genes shared by drug resistance and drug-induced EMT

BACKGROUND

In ovarian cancer (OC) therapy, even initially responsive patients develop drug resistance.

METHODS

Here, we present an OC cell model composed of variants with differing degrees of acquired resistance to carboplatin (CBP), cross-resistance to paclitaxel, and CBP-induced metastatic properties (migration and invasion). Transcriptome data were analysed by two approaches identifying differentially expressed genes and CBP sensitivity-correlating genes. The impact of selected genes and signalling pathways on drug resistance and metastatic potential, along with their clinical relevance, was examined by in vitro and in silico approaches.

RESULTS

TMEM200A and PRKAR1B were recognised as potentially involved in both phenomena, also having high predictive and prognostic values for OC patients. CBP-resistant MES-OV CBP8 cells were more sensitive to PI3K/Akt/mTOR pathway inhibitors Rapamycin, Wortmannin, SB216763, and transcription inhibitor Triptolide compared with parental MES-OV cells. When combined with CBP, Rapamycin decreased the sensitivity of parental cells while Triptolide sensitised drug-resistant cells to CBP. Four PI3K/Akt/mTOR inhibitors reduced migration in both cell lines.

CONCLUSIONS

A newly established research model and two distinct transcriptome analysis approaches identified novel candidate genes enrolled in CBP resistance development and/or CBP-induced EMT and implied that one-gene targeting could be a better approach than signalling pathway inhibition for influencing both phenomena.

Avian strains of emerging pathogen Escherichia fergusonii are phylogenetically diverse and harbor the greatest AMR dissemination potential among different sources: Comparative genomic evidence

Introduction

Escherichia fergusonii is regarded as an emerging pathogen with zoonotic potential. In the current study, we undertook source-wise comparative genomic analyses (resistome, virulome, mobilome and pangenome) to understand the antimicrobial resistance, virulence, mobile genetic elements and phylogenetic diversity of E. fergusonii.

Methods

Six E. fergusonii strains (5 multidrug resistant strains and 1 biofilm former) were isolated from poultry (duck faeces and retail chicken samples). Following confirmation by phenotypic and molecular methods, the isolates were further characterized and their genomes were sequenced. Comparative resisto-virulo-mobilome analyses and pangenomics were performed for E. fergusonii genomes, while including 125 other E. fergusonii genomes available from NCBI database.

Results and discussion

Avian and porcine strains of E. fergusonii were found to carry significantly higher number of antimicrobial resistance genes (p < 0.05) and mobile genetic elements (plasmids, transposons and integrons) (p < 0.05), while the pathogenic potential of bovine strains was significantly higher compared to other strains (p < 0.05). Pan-genome development trends indicated open pan-genome for all strains (0 < γ < 1). Genomic diversity of avian strains was found to be greater than that from other sources. Phylogenetic analysis revealed close clustering among isolates of similar isolation source and geographical location. Indian isolates of E. fergusonii clustered closely with those from Chinese and a singleton Australian isolate. Overall, being the first pangenomic study on E. fergusonii, our analysis provided important cues on genomic features of the emerging pathogen E. fergusonii while highlighting the potential role of avian strains in dissemination of AMR.

Seasonal variation of phytoplankton community assembly processes in Tibetan Plateau floodplain

Uncovering the mechanisms underlying phytoplankton community assembly remains a major challenge in freshwater ecology. The roles of environmental filtering and spatial processes in shaping phytoplankton metacommunity in Tibetan floodplain ecosystems under various hydrological conditions are still unclear. Here, multivariate statistics and a null model approach were used to compare the spatiotemporal patterns and assembly processes of phytoplankton communities in the river-oxbow lake system of Tibetan Plateau floodplain between non-flood and flood periods. The results showed that phytoplankton communities had significant seasonal and habitat variations, with the seasonal variations being more remarkable. Phytoplankton density, biomass, and alpha diversity were distinctly lower in the flood than non-flood period. The habitat differences (rivers vs. oxbow lakes) in phytoplankton community were less pronounced during the flood than non-flood period, most likely due to the increased hydrological connectivity. There was a significant distance-decay relationship only in lotic phytoplankton communities, and such relationship was stronger in the non-flood than flood period. Variation partitioning and PER-SIMPER analysis showed that the relative role of environmental filtering and spatial processes affecting phytoplankton assemblages varied across hydrological periods, with environmental filtering dominating in the non-flood period and spatial processes in the flood period. These results suggest that the flow regime plays a key role in balancing environmental and spatial factors in shaping phytoplankton communities. This study contributes to a deeper understanding of ecological phenomena in highland floodplains and provides a theoretical basis for floodplain ecosystem maintenance and ecological health management.

Analysis of the response regulatory network of pepper genes under hydrogen peroxide stress

Hydrogen peroxide (H₂O₂) is a regulatory component related to plant signal transduction. To better understand the genome-wide gene expression response to H₂O₂ stress in pepper plants, a regulatory network of H₂O₂ stress-gene expression in pepper leaves and roots was constructed in the present study. We collected the normal tissues of leaves and roots of pepper plants after 40 days of H₂O₂ treatment and obtained the RNA-seq data of leaves and roots exposed to H₂O₂ for 0.5-24 h. By comparing the gene responses of pepper leaves and roots exposed to H₂O₂ stress for different time periods, we found that the response in roots reached the peak at 3 h, whereas the response in leaves reached the peak at 24 h after treatment, and the response degree in the roots was higher than that in the leaves. We used all datasets for K-means analysis and network analysis identified the clusters related to stress response and related genes. In addition, CaEBS1, CaRAP2, and CabHLH029 were identified through a co-expression analysis and were found to be strongly related to several reactive oxygen species-scavenging enzyme genes; their homologous genes in Arabidopsis showed important functions in response to hypoxia or iron uptake. This study provides a theoretical basis for determining the dynamic response process of pepper plants to H₂O₂ stress in leaves and roots, as well as for determining the critical time and the molecular mechanism of H₂O₂ stress response in leaves and roots. The candidate transcription factors identified in this study can be used as a reference for further experimental verification.

Identification of DDX60 as a Regulator of MHC-I Class Molecules in Colorectal Cancer

Immune checkpoint blockade (ICB) therapies induce durable responses in approximately 15% of colorectal cancer (CRC) patients who exhibit microsatellite instability-high (MSI-H) or deficient mismatch repair (dMMR). However, more than 80% of CRC patients do not respond to current immunotherapy. The main challenge with these patients is lack of MHC-I signaling to unmask their cancer cells so the immune cells can detect them. Here, we started by comparing IFNγ signature genes and MHC-I correlated gene lists to determine the potential candidates for MHC-I regulators. Then, the protein expression level of listed potential candidates in normal and cancer tissue was compared to select final candidates with enough disparity between the two types of tissues. ISG15 and DDX60 were further tested by wet-lab experiments. Overexpression of DDX60 upregulated the expression of MHC-I, while knockdown of DDX60 reduced the MHC-I expression in CRC cells. Moreover, DDX60 was downregulated in CRC tissues, and lower levels of DDX60 were associated with a poor prognosis. Our data showed that DDX60 could regulate MHC-I expression in CRC; thus, targeting DDX60 may improve the effects of immunotherapy in some patients.

Pan-Cancer Analysis Identifies MNX1 and Associated Antisense Transcripts as Biomarkers for Cancer

The identification of diagnostic and prognostic biomarkers is a major objective in improving clinical outcomes in cancer, which has been facilitated by the availability of high-throughput gene expression data. A growing interest in non-coding genomic regions has identified dysregulation of long non-coding RNAs (lncRNAs) in several malignancies, suggesting a potential use as biomarkers. In this study, we leveraged data from large-scale sequencing projects to uncover the expression patterns of the MNX1 gene and its associated lncRNAs MNX1-AS1 and MNX1-AS2 in solid tumours. Despite many reports describing MNX1 overexpression in several cancers, limited studies exist on MNX1-AS1 and MNX1-AS2 and their potential as biomarkers. By employing clustering methods to visualise multi-gene relationships, we identified a discriminative power of the three genes in distinguishing tumour vs. normal samples in several cancers of the gastrointestinal tract and reproductive systems, as well as in discerning oesophageal and testicular cancer histological subtypes. Notably, the expressions of MNX1 and its antisenses also correlated with clinical features and endpoints, uncovering previously unreported associations. This work highlights the advantages of using combinatory expression patterns of non-coding transcripts of differentially expressed genes as clinical evaluators and identifies MNX1, MNX1-AS1, and MNX1-AS2 expressions as robust candidate biomarkers for clinical applications.

Transcriptome data reveal gene clusters and key genes in pepper response to heat shock

Climate change and global warming pose a great threat to plant growth and development as well as crop productivity. To better study the genome-wide gene expression under heat, we performed a time-course (0.5 to 24 h) transcriptome analysis in the leaf and root of 40-day-old pepper plants under 40°C as well as in control plants. Clustering analysis (K-means) showed that the expression of 29,249 genes can be grouped into 12 clusters with distinct expression dynamics under stress. Gene ontology (GO) enrichment analysis and transcription factor (TF) identification were performed on the clusters with certain expression patterns. Comparative analysis between the heat-treated and control plants also identified differentially expressed genes (DEGs), which showed the largest degree of change at 24 h. Interestingly, more DEGs were identified in the root than in the leaf. Moreover, we analyzed the gene expression of 25 heat shock factor genes (HSFs) in pepper after heat stress, identified five of these HSFs that responded to heat stress, and characterized the role of these genes in heat-tolerant (17CL30) and heat-susceptible (05S180) pepper lines. The findings of this study improve our understanding of the genome-wide heat stress response in pepper.

Proteomic and functional characterization of intra-tumor heterogeneity in human endometrial cancer

Endometrial cancer is one of the most frequently diagnosed gynecological cancers worldwide, and its prevalence has increased by more than 50% over the last two decades. Despite the understanding of the major signaling pathways driving the growth and metastasis of endometrial cancer, clinical trials targeting these signals have reported poor outcomes. The heterogeneous nature of endometrial cancer is suspected to be one of the key reasons for the failure of targeted therapies. In this study, we perform a sequential window acquisition of all theoretical fragment ion spectra (SWATH)-based comparative proteomic analysis of 63 tumor biopsies collected from 20 patients and define differences in protein signature in multiple regions of the same tumor. We develop organoids from multiple biopsies collected from the same tumor and show that organoids capture heterogeneity in endometrial cancer growth. Overall, using quantitative proteomics and patient-derived organoids, we define the heterogeneous nature of endometrial cancer within a patient’s tumor.

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Proteomic analysis of endometrial cancer intra-tumor heterogeneity

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Identification of potential biomarkers of tumor volume and invasion

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Protein signatures correlate with pre-and postmenopausal cancers

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Patient-derived organoids capture endometrial cancer heterogeneity

Effects of Immunoglobulins G From Systemic Sclerosis Patients in Normal Dermal Fibroblasts: A Multi-Omics Study

Autoantibodies (Aabs) are frequent in systemic sclerosis (SSc). Although recognized as potent biomarkers, their pathogenic role is debated. This study explored the effect of purified immunoglobulin G (IgG) from SSc patients on protein and mRNA expression of dermal fibroblasts (FBs) using an innovative multi-omics approach. Dermal FBs were cultured in the presence of sera or purified IgG from patients with diffuse cutaneous SSc (dcSSc), limited cutaneous SSc or healthy controls (HCs). The FB proteome and transcriptome were explored using liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) and microarray assays, respectively. Proteomic analysis identified 3,310 proteins. SSc sera and purified IgG induced singular protein profile patterns. These FB proteome changes depended on the Aab serotype, with a singular effect observed with purified IgG from anti-topoisomerase-I autoantibody (ATA) positive patients compared to HC or other SSc serotypes. IgG from ATA positive SSc patients induced enrichment in proteins involved in focal adhesion, cadherin binding, cytosolic part, or lytic vacuole. Multi-omics analysis was performed in two ways: first by restricting the analysis of the transcriptomic data to differentially expressed proteins; and secondly, by performing a global statistical analysis integrating proteomics and transcriptomics. Transcriptomic analysis distinguished 764 differentially expressed genes and revealed that IgG from dcSSc can induce extracellular matrix (ECM) remodeling changes in gene expression profiles in FB. Global statistical analysis integrating proteomics and transcriptomics confirmed that IgG from SSc can induce ECM remodeling and activate FB profiles. This effect depended on the serotype of the patient, suggesting that SSc Aab might play a pathogenic role in some SSc subsets.

An equivalence test between features lists, based on the Sorensen-Dice index and the joint frequencies of GO term enrichment

Background

In integrative bioinformatic analyses, it is of great interest to stablish the equivalence between gene or (more in general) feature lists, up to a given level and in terms of their annotations in the Gene Ontology. The aim of this article is to present an equivalence test based on the proportion of GO terms which are declared as enriched in both lists simultaneously.

Results

On the basis of these data, the dissimilarity between gene lists is measured by means of the Sorensen–Dice index. We present two flavours of the same test: One of them based on the asymptotic normality of the test statistic and the other based on the bootstrap method.

Conclusions

The accuracy of these tests is studied by means of simulation and their possible interest is illustrated by using them over two real datasets: A collection of gene lists related to cancer and a collection of gene lists related to kidney rejection after transplantation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-022-04739-2.

Machine-Learning-Based Genome-Wide Association Studies for Uncovering QTL Underlying Soybean Yield and Its Components

A genome-wide association study (GWAS) is currently one of the most recommended approaches for discovering marker-trait associations (MTAs) for complex traits in plant species. Insufficient statistical power is a limiting factor, especially in narrow genetic basis species, that conventional GWAS methods are suffering from. Using sophisticated mathematical methods such as machine learning (ML) algorithms may address this issue and advance the implication of this valuable genetic method in applied plant-breeding programs. In this study, we evaluated the potential use of two ML algorithms, support-vector machine (SVR) and random forest (RF), in a GWAS and compared them with two conventional methods of mixed linear models (MLM) and fixed and random model circulating probability unification (FarmCPU), for identifying MTAs for soybean-yield components. In this study, important soybean-yield component traits, including the number of reproductive nodes (RNP), non-reproductive nodes (NRNP), total nodes (NP), and total pods (PP) per plant along with yield and maturity, were assessed using a panel of 227 soybean genotypes evaluated at two locations over two years (four environments). Using the SVR-mediated GWAS method, we were able to discover MTAs colocalized with previously reported quantitative trait loci (QTL) with potential causal effects on the target traits, supported by the functional annotation of candidate gene analyses. This study demonstrated the potential benefit of using sophisticated mathematical approaches, such as SVR, in a GWAS to complement conventional GWAS methods for identifying MTAs that can improve the efficiency of genomic-based soybean-breeding programs.

Analysis of the Expression and Function of Key Genes in Pepper Under Low-Temperature Stress

The mechanism of resistance of plants to cold temperatures is very complicated, and the molecular mechanism and related gene network in pepper are largely unknown. Here, during cold treatment, we used cluster analysis (k-means) to classify all expressed genes into 15 clusters, 3,680 and 2,405 differentially expressed genes (DEGs) were observed in the leaf and root, respectively. The DEGs associated with certain important basic metabolic processes, oxidoreductase activity, and overall membrane compositions were most significantly enriched. In addition, based on the homologous sequence alignment of Arabidopsis genes, we identified 14 positive and negative regulators of the ICE-CBF-COR module in pepper, including CBF and ICE, and compared their levels in different data sets. The correlation matrix constructed based on the expression patterns of whole pepper genes in leaves and roots after exposure to cold stress showed the correlation between 14 ICE-CBF-COR signaling module genes, and provided insight into the relationship between these genes in pepper. These findings not only provide valuable resources for research on cold tolerance, but also lay the foundation for the genetic modification of cold stress regulators, which would help us achieve improved crop tolerance. To our knowledge, this is the first study to demonstrate the relationship between positive and negative regulators related to the ICE-CBF-COR module, which is of great significance to the study of low-temperature adaptive mechanisms in plants.

Changes in root microbiome during wheat evolution

Background

Although coevolutionary signatures of host-microbe interactions are considered to engineer the healthy microbiome of humans, little is known about the changes in root-microbiome during plant evolution. To understand how the composition of the wheat and its ancestral species microbiome have changed over the evolutionary processes, we performed a 16S rRNA metagenomic analysis on rhizobacterial communities associated with a phylogenetic framework of four Triticum species T. urartu, T. turgidum, T. durum, and T. aestivum along with their ancestral species Aegilops speltoides, and Ae. tauschii during vegetative and reproductive stages.

Results

In this study, we illustrated that the genome contents of wild species Aegilops speltoides and Ae. tauschii can be significant factors determining the composition of root-associated bacterial communities in domesticated bread wheat. Although it was found that domestication and modern breeding practices might have had a significant impact on microbiome-plant interactions especially at the reproductive stage, we observed an extensive and selective control by wheat genotypes on associated rhizobacterial communities at the same time. Our data also showed a strong genotypic variation within species of T. aestivum and Ae. tauschii, suggesting potential breeding targets for plants surveyed.

Conclusions

This study performed with different genotypes of Triticum and Aegilops species is the first study showing that the genome contents of Ae. speltoides and Ae. tauschii along with domestication-related changes can be significant factors determining the composition of root-associated bacterial communities in bread wheat. It is also indirect evidence that shows a very extensive range of host traits and genes are probably involved in host-microbe interactions. Therefore, understanding the wheat root-associated microbiome needs to take into consideration of its polygenetic mosaic nature.

Uncovering a Hub Signaling Pathway of Antimicrobial-Antifungal-Anticancer Peptides’ Axis on Short Cationic Peptides via Network Pharmacology Study

Short cationic peptides (SCPs) with therapeutic efficacy of antimicrobial peptides (AMPs), antifungal peptides (AFPs), and anticancer peptides (ACPs) are known as an enhancement of the host defense system. Here, we investigated the uppermost peptide(s), hub signaling pathway(s), and their associated target(s) through network pharmacology. Firstly, we selected SCPs with positive amino acid residues on N- and C- terminals under 500 Dalton via RStudio. Secondly, the overlapping targets between the bacteria-responsive targets (TTD and OMIM) and AMPs’ targets were visualized by VENNY 2.1. Thirdly, the overlapping targets between AFPs’ targets and fungal-responsive targets were exhibited by VENNY 2.1. Fourthly, the overlapping targets between cancer-related targets (TTD and OMIM) and fungal-responsive targets were displayed by VENNY 2.1. Finally, a molecular docking study (MDS) was carried out to discover the most potent peptides on a hub signaling pathway. A total of 1833 SCPs were identified, and AMPs’, AFPs’, and ACPs’ filtration suggested that 197 peptides (30 targets), 81 peptides (6 targets), and 59 peptides (4 targets) were connected, respectively. The AMPs―AFPs―ACPs’ axis indicated that 27 peptides (2 targets) were associated. Each hub signaling pathway for the enhancement of the host defense system was “Inactivation of Rap1 signaling pathway on AMPs”, “Activation of Notch signaling pathway on AMPs―AFPs’ axis”, and “Inactivation of HIF-1 signaling pathway on AMPs―AFPs―ACPs’ axis”. The most potent peptides were assessed via MDS; finally, HPIK on STAT3 and HVTK on NOS2 and on HIF-1 signaling pathway were the most stable complexes. Furthermore, the two peptides had better affinity scores than standard inhibitors (Stattic, 1400 W). Overall, the most potent SCPs for the human defense system were HPIK on STAT3 and HVTK on NOS2, which might inactivate the HIF-1 signaling pathway.

The characteristics and clinical significance of atypical mitosis in breast cancer

Atypical mitosis is considered a feature of malignancy, however, its significance in breast cancer (BC) remains elusive. Here, we aimed to assess the clinical value of atypical mitoses in BC and to explore their underlying molecular features. Atypical and typical mitotic figures were quantified and correlated with clinicopathological variables in a large cohort of primary BC tissue sections (n = 846) using digitalized hematoxylin and eosin whole-slide images (WSIs). In addition, atypical mitoses were assessed in The Cancer Genome Atlas (TCGA) BC dataset (n = 1032) and were linked to the genetic alterations and pathways. In this study, the median of typical mitoses was 17 per 3 mm² (range 0-120 mitoses), while the median of atypical mitoses was 4 (range 0-103 mitoses). High atypical mitoses were significantly associated with parameters characteristic of aggressive tumor behavior. The total number of mitoses, and a high atypical-to-typical mitoses ratio (>0.27) were associated with poor BC specific survival (BCSS), (p = 0.04 and 0.01, respectively). The atypical-to-typical mitoses ratio dichotomized triple negative-BC (TNBC) patients into two distinct groups in terms of the association with the outcome, while the overall number of mitoses was not. Moreover, TNBC patients with high atypical-to-typical mitoses ratio treated with adjuvant chemotherapy were associated with shorter survival (p = 0.003). Transcriptomic analysis of the TCGA-BRCA cohort dichotomized based on atypical mitoses identified 2494 differentially expressed genes. These included genes linked to pathways involved in chromosomal localization and segregation, centrosome assembly, spindle and microtubule formation, regulation of cell cycle and DNA repair. To conclude, the atypical-to-typical mitoses ratio has prognostic value independent of the overall mitotic count in BC patients and could predict the response to chemotherapy in TNBC.

Functional Genomics and Comparative Lineage-Specific Region Analyses Reveal Novel Insights into Race Divergence in Verticillium dahliae

Verticillium dahliae is a widespread soilborne fungus that causes Verticillium wilt on numerous economically important plant species. In tomato, until now, three races have been characterized based on the response of differential cultivars to V. dahliae, but the genetic basis of race divergence in V. dahliae remains undetermined. To investigate the genetic basis of race divergence, we sequenced the genomes of two race 2 strains and four race 3 strains for comparative analyses with two known race 1 genomes. The genetic basis of race divergence was described by the pathogenicity-related genes among the three races, orthologue analyses, and genomic structural variations. Global comparative genomics showed that chromosomal rearrangements are not the only source of race divergence and that race 3 should be split into two genotypes based on orthologue clustering. Lineage-specific regions (LSRs), frequently observed between genomes of the three races, encode several predicted secreted proteins that potentially function as suppressors of immunity triggered by known effectors. These likely contribute to the virulence of the three races. Two genes in particular that can act as markers for race 2 and race 3 (VdR2e and VdR3e, respectively) contribute to virulence on tomato, and the latter acts as an avirulence factor of race 3. We elucidated the genetic basis of race divergence through global comparative genomics and identified secreted proteins in LSRs that could potentially play critical roles in the differential virulence among the races in V. dahliae.

IMPORTANCE Deciphering the gene-for-gene relationships during host-pathogen interactions is the basis of modern plant resistance breeding. In the Verticillium dahliae-tomato pathosystem, two races (races 1 and 2) and their corresponding avirulence (Avr) genes have been identified, but strains that lack these two Avr genes exist in nature. In this system, race 3 has been described, but the corresponding Avr gene has not been identified. We de novo-sequenced genomes of six strains and identified secreted proteins within the lineage-specific regions (LSRs) distributed among the genomes of the three races that could potentially function as manipulators of host immunity. One of the LSR genes, VdR3e, was confirmed as the Avr gene for race 3. The results indicate that differences in transcriptional regulation may contribute to race differentiation. This is the first study to describe these differences and elucidate roles of secreted proteins in LSRs that play roles in race differentiation.

Pangenomic Analysis of Dickeya dianthicola Strains Related to the Outbreak of Blackleg and Soft Rot of Potato in the United States

Dickeya dianthicola has caused an outbreak of blackleg and soft rot of potato in the eastern half of the United States since 2015. To investigate genetic diversity of the pathogen, a comparative analysis was conducted on genomes of D. dianthicola strains. Whole genomes of 16 strains from the United States outbreak were assembled and compared with 16 previously sequenced genomes of D. dianthicola isolated from potato or carnation. Among the 32 strains, eight distinct clades were distinguished based on phylogenomic analysis. The outbreak strains were grouped into three clades, with the majority of the strains in clade I. Clade I strains were unique and homogeneous, suggesting a recent incursion of this strain into potato production from alternative hosts or environmental sources. The pangenome of the 32 strains contained 6,693 genes, 3,377 of which were core genes. By screening primary protein subunits associated with virulence from all U.S. strains, we found that many virulence-related gene clusters, such as plant cell wall degrading enzyme genes, flagellar and chemotaxis related genes, two-component regulatory genes, and type I/II/III secretion system genes, were highly conserved but that type IV and type VI secretion system genes varied. The clade I strains encoded two clusters of type IV secretion systems, whereas the clade II and III strains encoded only one cluster. Clade I and II strains encoded one more VgrG/PAAR spike protein than did clade III. Thus, we predicted that the presence of additional virulence-related genes may have enabled the unique clade I strain to become predominant in the U.S. outbreak.

The Perception of Rhizosphere Bacterial Communication Signals Leads to Transcriptome Reprogramming in Lysobacter capsici AZ78, a Plant Beneficial Bacterium

The rhizosphere is a dynamic region governed by complex microbial interactions where diffusible communication signals produced by bacteria continuously shape the gene expression patterns of individual species and regulate fundamental traits for adaptation to the rhizosphere environment. Lysobacter spp. are common bacterial inhabitants of the rhizosphere and have been frequently associated with soil disease suppressiveness. However, little is known about their ecology and how diffusible communication signals might affect their behavior in the rhizosphere. To shed light on the aspects determining rhizosphere competence and functioning of Lysobacter spp., we carried out a functional and transcriptome analysis on the plant beneficial bacterium Lysobacter capsici AZ78 (AZ78) grown in the presence of the most common diffusible communication signals released by rhizosphere bacteria. Mining the genome of AZ78 and other Lysobacter spp. showed that Lysobacter spp. share genes involved in the production and perception of diffusible signal factors, indole, diffusible factors, and N-acyl-homoserine lactones. Most of the tested diffusible communication signals (i.e., indole and glyoxylic acid) influenced the ability of AZ78 to inhibit the growth of the phytopathogenic oomycete Pythium ultimum and the Gram-positive bacterium Rhodococcus fascians. Moreover, RNA-Seq analysis revealed that nearly 21% of all genes in AZ78 genome were modulated by diffusible communication signals. 13-Methyltetradecanoic acid, glyoxylic acid, and 2,3-butanedione positively influenced the expression of genes related to type IV pilus, which might enable AZ78 to rapidly colonize the rhizosphere. Moreover, glyoxylic acid and 2,3-butanedione downregulated tRNA genes, possibly as a result of the elicitation of biological stress responses. On its behalf, indole downregulated genes related to type IV pilus and the heat-stable antifungal factor, which might result in impairment of twitching motility and antibiotic production in AZ78. These results show that diffusible communication signals may affect the ecology of Lysobacter spp. in the rhizosphere and suggest that diffusible communication signals might be used to foster rhizosphere colonization and functioning of plant beneficial bacteria belonging to the genus Lysobacter.

Microbeam Radiotherapy-A Novel Therapeutic Approach to Overcome Radioresistance and Enhance Anti-Tumour Response in Melanoma

Melanoma is the deadliest type of skin cancer, due to its invasiveness and limited treatment efficacy. The main therapy for primary melanoma and solitary organ metastases is wide excision. Adjuvant therapy, such as chemotherapy and targeted therapies are mainly used for disseminated disease. Radiotherapy (RT) is a powerful treatment option used in more than 50% of cancer patients, however, conventional RT alone is unable to eradicate melanoma. Its general radioresistance is attributed to overexpression of repair genes in combination with cascades of biochemical repair mechanisms. A novel sophisticated technique based on synchrotron-generated, spatially fractionated RT, called Microbeam Radiation Therapy (MRT), has been shown to overcome these treatment limitations by allowing increased dose delivery. With MRT, a collimator subdivides the homogeneous radiation field into an array of co-planar, high-dose microbeams that are tens of micrometres wide and spaced a few hundred micrometres apart. Different preclinical models demonstrated that MRT has the potential to completely ablate tumours, or significantly improve tumour control while dramatically reducing normal tissue toxicity. Here, we discuss the role of conventional RT-induced immunity and the potential for MRT to enhance local and systemic anti-tumour immune responses. Comparative gene expression analysis from preclinical tumour models indicated a specific gene signature for an 'MRT-induced immune effect'. This focused review highlights the potential of MRT to overcome the inherent radioresistance of melanoma which could be further enhanced for future clinical use with combined treatment strategies, in particular, immunotherapy.

BTK inhibition sensitizes Acute Lymphoblastic Leukemia to asparaginase by suppressing the Amino Acid Response pathway

CRISPR/Cas9 kinome screen identifies genes involved in ASNase sensitivity.

Ibrutinib synergizes with ASNase by inhibiting the amino acid response pathway via c-Myc– mediated regulation of GCN2.

Asparaginase (ASNase) therapy has been a mainstay of acute lymphoblastic leukemia (ALL) protocols for decades and shows promise in the treatment of a variety of other cancers. To improve the efficacy of ASNase treatment, we used a CRISPR/Cas9-based screen to identify actionable signaling intermediates that improve the response to ASNase. Both genetic inactivation of Bruton’s tyrosine kinase (BTK) and pharmacological inhibition by the BTK inhibitor ibrutinib strongly synergize with ASNase by inhibiting the amino acid response pathway, a mechanism involving c-Myc–mediated suppression of GCN2 activity. This synthetic lethal interaction was observed in 90% of patient-derived xenografts, regardless of the genomic subtype. Moreover, ibrutinib substantially improved ASNase treatment response in a murine PDX model. Hence, ibrutinib may be used to enhance the clinical efficacy of ASNase in ALL. This trial was registered at www.clinicaltrials.gov as # NCT02884453.

Effects of neoadjuvant therapies on genetic regulation of targeted pathways in ER+ primary ductal breast carcinoma: A meta-analysis of microarray datasets

Breast cancer arises as a result of multiple interactions between environmental and genetic factors. Conventionally, breast cancer is treated based on histopathological and clinical features. DNA technologies like the human genome microarray are now partially integrated into clinical practice and are used for developing new "personalized medicines" and "pharmacogenetics" for improving the efficiency and safety of cancer medications. We investigated the effects of four established therapies-for ER+ ductal breast cancer-on the differential gene expression. The therapies included single agent tamoxifen, two-agent docetaxel and capecitabine, or combined three-agents CAF (cyclophosphamide, doxorubicin, and fluorouracil) and CMF (cyclophosphamide, methotrexate, and fluorouracil). Genevestigator 8.1.0 was used to compare five datasets from patients with infiltrating ductal carcinoma, untreated or treated with selected drugs, to those from the healthy control. We identified 74 differentially expressed genes involved in three pathways, i.e., apoptosis (extrinsic and intrinsic), oxidative signaling, and PI3K/Akt signaling. The treatments affected the expression of apoptotic genes (TNFRSF10B [TRAIL], FAS, CASP3/6/7/8, PMAIP1 [NOXA], BNIP3L, BNIP3, BCL2A1, and BCL2), the oxidative stress-related genes (NOX4, XDH, MAOA, GSR, GPX3, and SOD3), and the PI3K/Akt pathway gene (ERBB2 [HER2]). Breast cancer treatments are complex with varying drug responses and efficacy among patients. This necessitates identifying novel biomarkers for predicting the drug response, using available data and new technologies. GSR, NOX4, CASP3, and ERBB2 are potential biomarkers for predicting the treatment response in primary ER+ ductal breast carcinoma.

Whole-Genome Sequence Data Analysis of Anoxybacillus kamchatkensis NASTPD13 Isolated from Hot Spring of Myagdi, Nepal

Anoxybacillus kamchatkensis NASTPD13 isolated from Paudwar hot spring of Myagdi, Nepal, upon morphological and biochemical analysis revealed to be Gram-positive, straight or slightly curved, rod-shaped, spore-forming, catalase, and oxidase-positive facultative anaerobes. It grows over a wide range of pH (5.0-11) and temperature (37-75°C), which showed growth in different reduced carbon sources such as starch raffinose, glucose, fructose, inositol, trehalose, sorbitol, mellobiose, and mannitol in aerobic conditions. Furthermore, the partial sequence obtained upon sequencing showed 99% sequence similarity in 16S rRNA gene sequence with A. kamchatkensis JW/VK-KG4 and was suggested to be Anoxybacillus kamchatkensis. Moreover, whole-genome analysis of NASTPD13 revealed 2,866,796 bp genome with a G+C content of 41.6%. Analysis of the genome revealed the presence of 102 RNA genes, which includes sequences coding for 19 rRNA and 79 tRNA genes. While the 16S rRNA gene sequence of strain NASTPD13 showed high similarity (>99%) to those of A. kamchatkensis JW/VK-KG4, RAST analysis of NASTPD13 genome suggested that A. kamchatkensis G10 is actually the closest neighbor in terms of sequence similarity. The genome annotation by RAST revealed various genes encoding glycoside hydrolases supporting that it can utilize several reduced carbon sources as observed and these genes could be important for carbohydrate-related industries. Xylanase pathway, particularly the genomic region encoding key enzymes for xylan depolymerization and xylose metabolism, further confirmed the presence of the complete gene in xylan metabolism. In addition, the complete xylose utilization gene locus analysis of NASTPD13 genome revealed all including D-xylose transport ATP-binding protein XylG and XylF, the xylose isomerase encoding gene XylA, and the gene XylB coding for a xylulokinase supported the fact that the isolate contains a complete set of genes related to xylan degradation, pentose transport, and metabolism. The results of the present study suggest that the isolated A. kamchatkensis NASTPD13 containing xylanase-producing genes could be useful in lignocellulosic biomass-utilizing industries where pentose polymers could also be utilized along with the hexose polymers.

Sulfitobacter alexandrii sp. nov., a new microalgae growth-promoting bacterium with exopolysaccharides bioflocculanting potential isolated from marine phycosphere

Marine phycosphere harbors unique cross-kingdom associations with enormous ecological significance in aquatic ecosystems as well as relevance for algal biotechnology industry. During our investigating the microbial composition and bioactivity of marine phycosphere microbiota (PM), a novel lightly yellowish and versatile bacterium designated strain AM1-D1^T was isolated from cultivable PM of marine dinoflagellate Alexandrium minutum amtk4 that produces high levels of paralytic shellfish poisoning toxins (PSTs). Strain AM1-D1^T demonstrates notable bioflocculanting bioactivity with bacterial exopolysaccharides (EPS), and microalgae growth-promoting (MGP) potential toward its algal host. Phylogenetic analysis based on 16S rRNA gene sequences revealed that strain AM1-D1^T was affiliated to the members of genus Sulfitobacter within the family Rhodobacteraceae, showing the highest sequence similarity of 97.9% with Sulfitobacter noctilucae NB-68^T, and below 97.8% with other type strains. The complete genome of strain AM1-D1^T consisted of a circular 3.84-Mb chromosome and five circular plasmids (185, 95, 15, 205 and 348 Kb, respectively) with the G+C content of 64.6%. Low values obtained by phylogenomic calculations on the average nucleotide identity (ANI, 77.2%), average amino acid identity (AAI, 74.7%) and digital DNA-DNA hybridization (dDDH, 18.6%) unequivocally separated strain AM1-D1^T from its closest relative. The main polar lipids were identified as phosphatidylglycerol, phosphatidylethanolamine, phosphatidylcholine, diphosphatidylglycerol, one unidentified phospholipid and one unidentified lipid. The predominant fatty acids (> 10%) were C_18:1 ω7c, C_19:0 cyclo ω8c and C_16:0. The respiratory quinone was Q-10. The genome of strain AM1-D1^T was predicted to encode series of gene clusters responsible for sulfur oxidation (sox) and utilization of dissolved organic sulfur exometabolites from marine dinoflagellates, taurine (tau) and dimethylsulfoniopropionate (DMSP) (dmd), as well as supplementary vitamin B₁₂ (cob), photosynthesis carotenoids (crt) which are pivotal components during algae-bacteria interactions. Based on the evidences by the polyphasic characterizations, strain AM1-D1^T represents a novel species of the genus Sulfitobacter, for which the name Sulfitobacter alexandrii sp. nov. is proposed. The type strain is AM1-D1^T (= CCTCC 2017277T = KCTC 62491^T).

Algal and cyanobacterial diversity in saline rivers of the Elton Lake Basin (Russia) studied via light microscopy and next-generation sequencing

Naturally saline rivers are known in various regions of the world. Saline rivers with a salinity gradient from the source to the mouth are particularly interesting, because the range of salinity is the structure-forming factor of the hydrobiont assemblage. Such rivers are represented by saline rivers of the Elton Lake Basin in Volgograd region of Russia (the Bolshaya Samoroda River and the Malaya Samoroda River). Herein, we analyzed taxonomic structure and species diversity of microalgae and Cyanobacteria of the saline rivers flowing into the Elton Lake by light microscopy and next-generation sequencing. The differences and possible causes of inconsistencies in the results obtained by these methods are discussed. In total, 91 taxa of microorganisms were identified by integrated approach in the assemblages of microalgae and Cyanobacteria in the middle course of the Bolshaya Samoroda River, and 60 taxa – in the river mouth. The species diversity of those assemblages in the hypersaline Malaya Samoroda River was lower: 27 taxa from the middle course and 23 taxa from the mouth. Next-generation sequencing allowed us to refine and expand the list of microalgae taxa in the studied saline rivers due to detection of species which were hard to identify, low-abundance taxa, as well as extremely small-cell forms. Some discrepancies between the data obtained by light microscopy and next-generation sequencing indicate the advantage of simultaneous use of both methods for study of the algae communities. Such a comprehensive approach provides the most accurate and correct list of taxa added with the morphological descriptions and 18S rRNA and 16S rRNA partial sequences. Generally, 18 taxa have been recorded for the first time in the Bolshaya Samoroda River, belonging to the phyla Chlorophyta (Borodinellopsis sp., Chlorochytrium lemnae Cohn, Caespitella sp., Halochlorococcum sp., Tetraselmis cordiformis (H. J. Carter) F. Stein), Ochrophyta (Pseudocharaciopsis ovalis (Chodat) D. J. Hibberd, Characiopsis sp., Poterioochromonas stipitata Scherffel, Chrysolepidomonas sp.), Euglenozoa (Euglena bucharica I. Kisselev, Lepocinclis tripteris (Dujardin) B. Marin & Melkonian, Phacus orbicularis K. Hübner, P. parvulus G. A. Klebs), Cryptophyta (Hemiselmis cryptochromatica C. E. Lane & J. M. Archibald, Rhodomonas sp., Hanusia phi J. A. Deane), Haptophyta (Pavlova sp.), Cyanobacteria (Johanseninema constrictum (Szafer) Hasler, Dvorák & Poulícková). Seven taxa have been detected for the first time in the algal and cyanobacterial assemblages of the Malaya Samoroda River from the phyla Chlorophyta (Tetraselmis cordiformis, T. arnoldii (Proschkina-Lavrenko) R. E. Norris, Hori & Chihara, T. tetrathele (West) Butcher, Pyrobotrys elongatus Korshikov), Cryptophyta (Hanusia phi), and Cyanobacteria (Synechococcus elongatus (Nägeli) Nägeli, Oscillatoria simplicissima Gomont).

Co-expression network analysis of protein phosphatase 2A (PP2A) genes with stress-responsive genes in Arabidopsis thaliana reveals 13 key regulators

Abiotic and biotic stresses adversely affect plant growth and development and eventually result in less yield and threaten food security worldwide. In plants, several studies have been carried out to understand molecular responses to abiotic and biotic stresses. However, the complete circuitry of stress-responsive genes that plants utilise in response to those environmental stresses are still unknown. The protein phosphatase 2A (PP2A) gene has been known to have a crucial role in abiotic and biotic stresses; but how it regulates the stress response in plants is still not known completely. In this study, we constructed gene co-expression networks of PP2A genes with stress-responsive gene datasets from cold, drought, heat, osmotic, genotoxic, salt, and wounding stresses to unveil their relationships with the PP2A under different conditions of stress. The graph analysis identified 13 hub genes and several influential genes based on closeness centrality score (CCS). Our findings also revealed the count of unique genes present in different settings of stresses and subunits. We also formed clusters of influential genes based on the stress, CCS, and co-expression value. Analysis of cis-regulatory elements (CREs), recurring in promoters of these genes was also performed. Our study has led to the identification of 16 conserved CREs.

Phenotypic and Transcriptomic Analyses of Seven Clinical Stenotrophomonas maltophilia Isolates Identify a Small Set of Shared and Commonly Regulated Genes Involved in the Biofilm Lifestyle

Stenotrophomonas maltophilia is one of the most frequently isolated multidrug-resistant nosocomial opportunistic pathogens. It contributes to disease progression in cystic fibrosis (CF) patients and is frequently isolated from wounds, infected tissues, and catheter surfaces. On these diverse surfaces S. maltophilia lives in single-species or multispecies biofilms. Since very little is known about common processes in biofilms of different S. maltophilia isolates, we analyzed the biofilm profiles of 300 clinical and environmental isolates from Europe of the recently identified main lineages Sgn3, Sgn4, and Sm2 to Sm18. The analysis of the biofilm architecture of 40 clinical isolates revealed the presence of multicellular structures and high phenotypic variability at a strain-specific level. Further, transcriptome analyses of biofilm cells of seven clinical isolates identified a set of 106 shared strongly expressed genes and 33 strain-specifically expressed genes. Surprisingly, the transcriptome profiles of biofilm versus planktonic cells revealed that just 9.43% ± 1.36% of all genes were differentially regulated. This implies that just a small set of shared and commonly regulated genes is involved in the biofilm lifestyle. Strikingly, iron uptake appears to be a key factor involved in this metabolic shift. Further, metabolic analyses implied that S. maltophilia employs a mostly fermentative growth mode under biofilm conditions. The transcriptome data of this study together with the phenotypic and metabolic analyses represent so far the largest data set on S. maltophilia biofilm versus planktonic cells. This study will lay the foundation for the identification of strategies for fighting S. maltophilia biofilms in clinical and industrial settings.IMPORTANCE Microorganisms living in a biofilm are much more tolerant to antibiotics and antimicrobial substances than planktonic cells are. Thus, the treatment of infections caused by microorganisms living in biofilms is extremely difficult. Nosocomial infections (among others) caused by S. maltophilia, particularly lung infection among CF patients, have increased in prevalence in recent years. The intrinsic multidrug resistance of S. maltophilia and the increased tolerance to antimicrobial agents of its biofilm cells make the treatment of S. maltophilia infection difficult. The significance of our research is based on understanding the common mechanisms involved in biofilm formation of different S. maltophilia isolates, understanding the diversity of biofilm architectures among strains of this species, and identifying the differently regulated processes in biofilm versus planktonic cells. These results will lay the foundation for the treatment of S. maltophilia biofilms.

RainBio: Proportional Visualization of Large Sets in Biology

Set visualization is a well-known task in information visualization. In biology, it is used for comparing visually sets of genes or proteins, typically using Venn diagrams. However, limitations of the Venn diagram are well-known: they are limited to 6 sets and difficult to read above 4. Many other set visualization techniques have been proposed, but they have never been widely used in biology. In this paper, we introduce RainBio, a technique for visualizing sets in biology and aimed at providing a global overview showing the size of the main intersections, in a proportional way, and the similarities between sets. We adapt rainbow boxes, a technique for visualizing small datasets, to the visualization of larger sets, using element aggregation and intersection clustering. We present the application of RainBio to three datasets, with 5, 6 and 12 sets. We also describe a small user study comparing RainBio with Venn diagrams, involving 30 students in biology. Results showed that RainBio led to significantly fewer errors on 6-set dataset, and that the majority of students preferred RainBio. RainBio is proposed as a web-based tool for up to 15 sets.

Whole genome sequencing data of multiple individuals of Pakistani descent

Here we report whole genome sequencing of four individuals (H3, H4, H5, and H6) from a family of Pakistani descent. Whole genome sequencing yielded 1084.92, 894.73, 1068.62, and 1005.77 million mapped reads corresponding to 162.73, 134.21, 160.29, and 150.86 Gb sequence data and 52.49x, 43.29x, 51.70x, and 48.66x average coverage for H3, H4, H5, and H6, respectively. We identified 3,529,659, 3,478,495, 3,407,895, and 3,426,862 variants in the genomes of H3, H4, H5, and H6, respectively, including 1,668,024 variants common in the four genomes. Further, we identified 42,422, 39,824, 28,599, and 35,206 novel variants in the genomes of H3, H4, H5, and H6, respectively. A major fraction of the variants identified in the four genomes reside within the intergenic regions of the genome. Single nucleotide polymorphism (SNP) genotype based comparative analysis with ethnic populations of 1000 Genomes database linked the ancestry of all four genomes with the South Asian populations, which was further supported by mitochondria based haplogroup analysis. In conclusion, we report whole genome sequencing of four individuals of Pakistani descent.

Measurement(s)	SNV • genome
Technology Type(s)	whole genome sequencing • DNA sequencing
Factor Type(s)	individual
Sample Characteristic - Organism	Homo sapiens
Sample Characteristic - Location	Pakistan

Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.12642761

Transcriptomic analysis at organ and time scale reveals gene regulatory networks controlling the sulfate starvation response of Solanum lycopersicum

BACKGROUND

Sulfur is a major component of biological molecules and thus an essential element for plants. Deficiency of sulfate, the main source of sulfur in soils, negatively influences plant growth and crop yield. The effect of sulfate deficiency on plants has been well characterized at the physiological, transcriptomic and metabolomic levels in Arabidopsis thaliana and a limited number of crop plants. However, we still lack a thorough understanding of the molecular mechanisms and regulatory networks underlying sulfate deficiency in most plants. In this work we analyzed the impact of sulfate starvation on the transcriptome of tomato plants to identify regulatory networks and key transcriptional regulators at a temporal and organ scale.

RESULTS

Sulfate starvation reduces the growth of roots and leaves which is accompanied by major changes in the organ transcriptome, with the response being temporally earlier in roots than leaves. Comparative analysis showed that a major part of the Arabidopsis and tomato transcriptomic response to sulfate starvation is conserved between these plants and allowed for the identification of processes specifically regulated in tomato at the transcript level, including the control of internal phosphate levels. Integrative gene network analysis uncovered key transcription factors controlling the temporal expression of genes involved in sulfate assimilation, as well as cell cycle, cell division and photosynthesis during sulfate starvation in tomato roots and leaves. Interestingly, one of these transcription factors presents a high identity with SULFUR LIMITATION1, a central component of the sulfate starvation response in Arabidopsis.

CONCLUSIONS

Together, our results provide the first comprehensive catalog of sulfate-responsive genes in tomato, as well as novel regulatory targets for future functional analyses in tomato and other crops.

A critical role of PRDM14 in human primordial germ cell fate revealed by inducible degrons

PRDM14 is a crucial regulator of mouse primordial germ cells (mPGCs), epigenetic reprogramming and pluripotency, but its role in the evolutionarily divergent regulatory network of human PGCs (hPGCs) remains unclear. Besides, a previous knockdown study indicated that PRDM14 might be dispensable for human germ cell fate. Here, we decided to use inducible degrons for a more rapid and comprehensive PRDM14 depletion. We show that PRDM14 loss results in significantly reduced specification efficiency and an aberrant transcriptome of hPGC-like cells (hPGCLCs) obtained in vitro from human embryonic stem cells (hESCs). Chromatin immunoprecipitation and transcriptomic analyses suggest that PRDM14 cooperates with TFAP2C and BLIMP1 to upregulate germ cell and pluripotency genes, while repressing WNT signalling and somatic markers. Notably, PRDM14 targets are not conserved between mouse and human, emphasising the divergent molecular mechanisms of PGC specification. The effectiveness of degrons for acute protein depletion is widely applicable in various developmental contexts.

A-Lister: a tool for analysis of differentially expressed omics entities across multiple pairwise comparisons

BACKGROUND

Researchers commonly analyze lists of differentially expressed entities (DEEs), such as differentially expressed genes (DEGs), differentially expressed proteins (DEPs), and differentially methylated positions/regions (DMPs/DMRs), across multiple pairwise comparisons. Large biological studies can involve multiple conditions, tissues, and timepoints that result in dozens of pairwise comparisons. Manually filtering and comparing lists of DEEs across multiple pairwise comparisons, typically done by writing custom code, is a cumbersome task that can be streamlined and standardized.

RESULTS

A-Lister is a lightweight command line and graphical user interface tool written in Python. It can be executed in a differential expression mode or generic name list mode. In differential expression mode, A-Lister accepts as input delimited text files that are output by differential expression tools such as DESeq2, edgeR, Cuffdiff, and limma. To allow for the most flexibility in input ID types, to avoid database installation requirements, and to allow for secure offline use, A-Lister does not validate or impose restrictions on entity ID names. Users can specify thresholds to filter the input file(s) by column(s) such as p-value, q-value, and fold change. Additionally, users can filter the pairwise comparisons within the input files by fold change direction (sign). Queries composed of intersection, fuzzy intersection, difference, and union set operations can also be performed on any number of pairwise comparisons. Thus, the user can filter and compare any number of pairwise comparisons within a single A-Lister differential expression command. In generic name list mode, A-Lister accepts delimited text files containing lists of names as input. Queries composed of intersection, fuzzy intersection, difference, and union set operations can then be performed across these lists of names.

CONCLUSIONS

A-Lister is a flexible tool that enables the user to rapidly narrow down large lists of DEEs to a small number of most significant entities. These entities can then be further analyzed using visualization, pathway analysis, and other bioinformatics tools.

Halorientalis pallida sp. nov., an extremely halophilic archaeon isolated from a marine saltern

An extremely halophilic archaeon, strain F13-25^T, was isolated from a marine saltern located in Isla Cristina, Huelva, on the south-west coast of Spain. The novel strain had pink-pigmented, non-motile, coccoid cells. Optimal growth was achieved at 25 % (w/v) NaCl, pH 7.5 and 37 °C. Strain F13-25^T possessed two heterogeneous 16S rRNA genes (rrnA and rrnB) most closely related to Halorientalis persicus D108^T (97.6-99.2 % sequence similarity) and Halorientalis regularis TNN28^T (95.9-98.8 %). On the basis of the results of rpoB' gene sequence analysis, strain F13-25^T was also closely related to Halorientalis persicus IBRC-M 10043^T (89.9 %) and Halorientalis regularis TNN28^T (92.3 %). Relatedness values, computed using the Genome-to-Genome Distance Calculator, between strain F13-25^T and Halorientalis persicus IBRC-M 10043^T and Halorientalis regularis IBRC-M 10760^T were 34.6 and 36.2 %, respectively. Average nucleotide identity values based on orthoANI, ANIb and ANIm of strain F13-25^T and Halorientalis persicus IBRC-M 10043^T and Halorientalisregularis IBRC-M 10760^T were 88.0 and 88.8, 87.1 and 87.6 %, and 89.2 and 89.6 %, respectively. All values were far below the threshold accepted for prokaryotic species delineation. The major polar lipids were phosphatidylglycerol, phosphatidylglycerol phosphate methyl ester and one glycolipid chromatographically identical to sulfated diglycosyl diether. The DNA G+C content was 65.7 mol% (genome). The results of phylogenetic, phenotypic and chemotaxonomic analyses indicated that strain F13-25^T represents a novel species of the genus Halorientalis, for which the name Halorientalis pallida sp. nov., with type strain F13-25^T (=CECT 9384^T=IBRC-M 11176^T), is proposed.

An equivalence approach to the integrative analysis of feature lists

BACKGROUND

Although a few comparison methods based on the biological meaning of gene lists have been developed, the goProfiles approach is one of the few that are being used for that purpose. It consists of projecting lists of genes into predefined levels of the Gene Ontology, in such a way that a multinomial model can be used for estimation and testing. Of particular interest is the fact that it may be used for proving equivalence (in the sense of "enough similarity") between two lists, instead of proving differences between them, which seems conceptually better suited to the end goal of establishing similarity among gene lists. An equivalence method has been derived that uses a distance-based approach and the confidence interval inclusion principle. Equivalence is declared if the upper limit of a one-sided confidence interval for the distance between two profiles is below a pre-established equivalence limit.

RESULTS

In this work, this method is extended to establish the equivalence of any number of gene lists. Additionally, an algorithm to obtain the smallest equivalence limit that would allow equivalence between two or more lists to be declared is presented. This algorithm is at the base of an iterative method of graphic visualization to represent the most to least equivalent gene lists. These methods deal adequately with the problem of adjusting for multiple testing. The applicability of these techniques is illustrated in two typical situations: (i) a collection of cancer-related gene lists, suggesting which of them are more reasonable to combine -as claimed by the authors- and (ii) a collection of pathogenesis-based transcript sets, showing which of these are more closely related. The methods developed are available in the goProfiles Bioconductor package.

CONCLUSIONS

The method provides a simple yet powerful and statistically well-grounded way to classify a set of genes or other feature lists by establishing their equivalence at a given equivalence threshold. The classification results can be viewed using standard visualization methods. This may be applied to a variety of problems, from deciding whether a series of datasets generating the lists can be combined to the simplification of groups of lists.

Proteomic Analysis of Stromal and Epithelial Cell Communications in Human Endometrial Cancer Using a Unique 3D Co-Culture Model

Epithelial and stromal communications are essential for normal uterine functions and their dysregulation contributes to the pathogenesis of many diseases including infertility, endometriosis, and cancer. Although many studies have highlighted the advantages of culturing cells in 3D compared to the conventional 2D culture system, one of the major limitations of these systems is the lack of incorporation of cells from non-epithelial lineages. In an effort to develop a culture system incorporating both stromal and epithelial cells, 3D endometrial cancer spheroids are developed by co-culturing endometrial stromal cells with cancerous epithelial cells. The spheroids developed by this method are phenotypically comparable to in vivo endometrial cancer tissue. Proteomic analysis of the co-culture spheroids comparable to human endometrial tissue revealed 591 common proteins and canonical pathways that are closely related to endometrium biology. To determine the feasibility of using this model for drug screening, the efficacy of tamoxifen and everolimus is tested. In summary, a unique 3D model system of human endometrial cancer is developed that will serve as the foundation for the further development of 3D culture systems incorporating different cell types of the human uterus for deciphering the contributions of non-epithelial cells present in cancer microenvironment.

DNA methylation profiling implicates exposure to PCBs in the pathogenesis of B-cell chronic lymphocytic leukemia

OBJECTIVES

To characterize the impact of PCB exposure on DNA methylation in peripheral blood leucocytes and to evaluate the corresponding changes in relation to possible health effects, with a focus on B-cell lymphoma.

METHODS

We conducted an epigenome-wide association study on 611 adults free of diagnosed disease, living in Italy and Sweden, in whom we also measured plasma concentrations of 6 PCB congeners, DDE and hexachlorobenzene.

RESULTS

We identified 650 CpG sites whose methylation correlates strongly (FDR < 0.01) with plasma concentrations of at least one PCB congener. Stronger effects were observed in males and in Sweden. This epigenetic exposure profile shows extensive and highly statistically significant overlaps with published profiles associated with the risk of future B-cell chronic lymphocytic leukemia (CLL) as well as with clinical CLL (38 and 28 CpG sites, respectively). For all these sites, the methylation changes were in the same direction for increasing exposure and for higher disease risk or clinical disease status, suggesting an etiological link between exposure and CLL. Mediation analysis reinforced the suggestion of a causal link between exposure, changes in DNA methylation and disease. Disease connectivity analysis identified multiple additional diseases associated with differentially methylated genes, including melanoma for which an etiological link with PCB exposure is established, as well as developmental and neurological diseases for which there is corresponding epidemiological evidence. Differentially methylated genes include many homeobox genes, suggesting that PCBs target stem cells. Furthermore, numerous polycomb protein target genes were hypermethylated with increasing exposure, an effect known to constitute an early marker of carcinogenesis.

CONCLUSIONS

This study provides mechanistic evidence in support of a link between exposure to PCBs and the etiology of CLL and underlines the utility of omic profiling in the evaluation of the potential toxicity of environmental chemicals.

Integrated network analysis and machine learning approach for the identification of key genes of triple-negative breast cancer

Triple-negative breast cancer (TNBC) has attracted more attention compared with other breast cancer subtypes due to its aggressive nature, poor prognosis, and chemotherapy remains the mainstay of treatment with no other approved targeted therapy. Therefore, the study aimed to discover more promising therapeutic targets and investigating new insights of biological mechanism of TNBC. Six microarray data sets consisting of 463 non-TNBC and 405 TNBC samples were mined from Gene Expression Omnibus. The data sets were integrated by meta-analysis and identified 1075 differentially expressed genes. Protein-protein interaction network was constructed which consists of 486 nodes and 1932 edges, where 29 hub genes were obtained with high topological measures. Further, 16 features (hub genes), 12 upregulated (AURKB, CCNB2, CDC20, DDX18, EGFR, ENO1, MYC, NUP88, PLK1, PML, POLR2F, and SKP2) and four downregulated ( CCND1, GLI3, SKP1, and TGFB3) were selected through machine learning correlation based feature selection method on training data set. A naïve Bayes based classifier built using the expression profiles of 16 features (hub genes) accurately and reliably classify TNBC from non-TNBC samples in the validation test data set with a receiver operating curve of 0.93 to 0.98. Subsequently, Gene Ontology analysis revealed that the hub genes were enriched in mitotic cell cycle processes and Kyoto Encyclopedia of Genes and Genomes pathway analysis showed that they were enriched in cell cycle pathways. Thus, the identified key hub genes and pathways highlighted in the study would enhance the understanding of molecular mechanism of TNBC which may serve as potential therapeutic target.

Sequential Fractionation Strategy Identifies Three Missing Proteins in the Mitochondrial Proteome of Commonly Used Cell Lines

Mitochondria are undeniably the cell powerhouse, directly affecting cell survival and fate. Growing evidence suggest that mitochondrial protein repertoire affects metabolic activity and plays an important role in determining cell proliferation/differentiation or quiescence shift. Consequently, the bioenergetic status of a cell is associated with the quality and abundance of the mitochondrial populations and proteomes. Mitochondrial morphology changes in the development of different cellular functions associated with metabolic switches. It is therefore reasonable to speculate that different cell lines do contain different mitochondrial-associated proteins, and the investigation of these pools may well represent a source for mining missing proteins (MPs). A very effective approach to increase the number of IDs through mass spectrometry consists of reducing the complexity of the biological samples by fractionation. The present study aims at investigating the mitochondrial proteome of five phenotypically different cell lines, possibly expressing some of the MPs, through an enrichment-fractionation approach at the organelle and protein level. We demonstrate a substantial increase in the proteome coverage, which, in turn, increases the likelihood of detecting low abundant proteins, often falling in the category of MPs, and resulting, for the present study, in the identification of METTL12, FAM163A, and RGS13. All MS data have been deposited to the MassIVE data repository ( https://massive.ucsd.edu ) with the data set identifier MSV000082409 and PXD010446.

Salinivibrio kushneri sp. nov., a moderately halophilic bacterium isolated from salterns

Ten Gram-strain-negative, facultatively anaerobic, moderately halophilic bacterial strains, designated AL184^T, IB560, IB563, IC202, IC317, MA421, ML277, ML318, ML328A and ML331, were isolated from water ponds of five salterns located in Spain. The cells were motile, curved rods and oxidase and catalase positive. All of them grew optimally at 37°C, at pH 7.2-7.4 and in the presence of 7.5% (w/v) NaCl. Based on phylogenetic analyses of the 16S rRNA, the isolates were most closely related to Salinivibrio sharmensis BAG^T (99.6-98.2% 16S rRNA gene sequence similarity) and Salinivibrio costicola subsp. costicola ATCC 35508^T (99.0-98.1%). According to the MLSA analyses based on four (gyrB, recA, rpoA and rpoD) and eight (ftsZ, gapA, gyrB, mreB, pyrH, recA, rpoA and topA) concatenated gene sequences, the most closely relatives were S. siamensis JCM 14472^T (96.8-95.4% and 94.9-94.7%, respectively) and S. sharmensis DSM 18182^T (94.0-92.6% and 92.9-92.7%, respectively). In silico DNA-DNA hybridization (GGDC) and average nucleotide identity (ANI) showed values of 23.3-44.8% and 80.2-91.8%, respectively with the related species demonstrating that the ten isolates constituted a single novel species of the genus Salinivibrio. Its pangenome and core genome consist of 6041 and 1230 genes, respectively. The phylogeny based on the concatenated orthologous core genes revealed that the ten strains form a coherent phylogroup well separated from the rest of the species of the genus Salinivibrio. The major cellular fatty acids of strain AL184^T were C_16:0 and C_18:1. The DNA G+C content range was 51.9-52.5mol% (T_m) and 50.2-50.9mol% (genome). Based on the phylogenetic-phylogenomic, phenotypic and chemotaxonomic data, the ten isolates represent a novel species of the genus Salinivibrio, for which the name Salinivibrio kushneri sp. nov. is proposed. The type strain is AL184^T (=CECT 9177^T=LMG 29817^T).