Comparison of 16S rRNA gene sequencing microbiota among children with serological IgE-mediated food hypersensitivity.

BACKGROUND: We hypothesized that specific food hypersensitivity (FH) in children is linked to specific gut microbiota. The aim of our study was to quantify and evaluate differences in gut microbial composition among children with different IgE-mediated FH. METHODS: Children (n = 81) aged 18 to 36 months were enrolled, fecal samples of 57 children with FH and 24 healthy children were evaluated using next-generation sequencing. Individual microbial diversity and composition were analyzed via targeting the 16 S rRNA gene hypervariable V3-V5 regions. RESULTS: Children with IgE-mediated FH (in milk, egg white, soy) had significantly lower gut microbiota diversity and richness than healthy children. Children with IgE-mediated FH exhibited relatively high abundances of Firmicutes and relative underrepresentation of the phylum Bacteroidetes. We observed significant increases in relative abundances of Ruminococcaceae, Clostridiaceae, and Erysipelotrichaceae (p < 0.01, compared to control) in children with milk hypersensitivity and of Clostridiaceae and Erysipelotrichaceae (p < 0.01) in children with peanut hypersensitivity. We also found significant increases in the numbers of Clostridiaceae, Lachnospiraceae and Pasteurellaceae (p < 0.01) in children with egg white hypersensitivity. CONCLUSIONS: These findings identify early evidence of different gut microbiota development/ differentiation in children with food hypersensitivity. Specific food hypersensitivities may be associated with compositional changes in intestinal microbiota. IMPACT: These findings identify early evidence of different gut microbiota development/differentiation in children with food hypersensitivity. We built a gut microbial profile that could identify toddlers at risk for food hypersensitivity. Children with enriched Firmicutes (phylum) with partial different families may be associated with food hypersensitivity. Enriched family Clostridiaceae, Ruminococcaceae, Lachnospiraceae, or Erysipelotrichaceae in gut microbiota may be associated with specific food hypersensitivities (such as milk, egg white, peanut) in children.

Adequate antiviral treatment lowers overall complications of cytomegalovirus colitis among inpatients with inflammatory bowel diseases.

BACKGROUND: Cytomegalovirus (CMV) colitis significantly complicates the course of inflammatory bowel disease (IBD), frequently leading to severe flare-ups and poor outcomes. The role of antiviral therapy in hospitalized IBD patients with CMV colitis is currently under debate. This retrospective analysis seeks to clarify the influence of antiviral treatment on these patients. METHODS: We retrospectively reviewed IBD patients diagnosed with CMV colitis via immunohistochemistry staining from colonic biopsies at a major tertiary center from January 2000 to May 2021. The study focused on patient demographics, clinical features, risk factors, prognostic indicators, and antiviral treatment outcomes. RESULTS: Among 118 inpatients, 42 had CMV colitis. Risk factors included hypoalbuminemia and antibiotic use. IBD patients with CMV colitis receiving < 14 days of antiviral therapy had higher complication (72% vs. 43%, p = 0.028) and surgery rates (56% vs. 26%, p = 0.017) compared to those without CMV. Adequate antiviral therapy (≥ 14 days) significantly reduced complications in the CMV group (29% vs. 72%, p = 0.006), especially in Crohn's disease (20% vs. 100%, p = 0.015). Independent predictors of IBD-related complications were CMV colitis (Odds Ratio [OR] 3.532, 90% Confidence Interval [CI] 1.012-12.331, p = 0.048), biological treatment failure (OR 4.953, 95% CI 1.91-12.842, p = 0.001), and adequate antiviral therapy (OR 0.108, 95% CI 0.023-0.512, p = 0.005). CONCLUSION: CMV colitis and a history of biological treatment failure increase complication risks in IBD patients. Adequate antiviral therapy significantly mitigates these risks, highlighting its importance in managing IBD patients with CMV colitis.

HeapMS: An Automatic Peak-Picking Pipeline for Targeted Proteomic Data Powered by 2D Heatmap Transformation and Convolutional Neural Networks.

The process of peak picking and quality assessment for multiple reaction monitoring (MRM) data demands significant human effort, especially for signals with low abundance and high interference. Although multiple peak-picking software packages are available, they often fail to detect peaks with low quality and do not report cases with low confidence. Furthermore, visual examination of all chromatograms is still necessary to identify uncertain or erroneous cases. This study introduces HeapMS, a web service that uses artificial intelligence to assist with peak picking and the quality assessment of MRM chromatograms. HeapMS applies a rule-based filter to remove chromatograms with low interference and high-confidence peak boundaries detected by Skyline. Additionally, it transforms two histograms (representing light and heavy peptides) into a single encoded heatmap and performs a two-step evaluation (quality detection and peak picking) using image convolutional neural networks. HeapMS offers three categories of peak picking: uncertain peak picking that requires manual inspection, deletion peak picking that requires removal or manual re-examination, and automatic peak picking. HeapMS acquires the chromatogram and peak-picking boundaries directly from Skyline output. The output results are imported back into Skyline for further manual inspection, facilitating integration with Skyline. HeapMS offers the benefit of detecting chromatograms that should be deleted or require human inspection. Based on defined categories, it can significantly reduce human workload and provide consistent results. Furthermore, by using heatmaps instead of histograms, HeapMS can adapt to future updates in image recognition models. The HeapMS is available at: https://github.com/ccllabe/HeapMS.

Marine prebiotics mediate decolonization of Pseudomonas aeruginosa from gut by inhibiting secreted virulence factor interactions with mucins and enriching Bacteroides population.

BACKGROUND: Pseudomonas aeruginosa intestinal carriage rates are significantly higher in immunosuppressed individuals and hospitalized patients who therefore have increased risk of infections and antibiotic-associated diarrhea. To combat intestinal dysbiosis and decolonize P. aeruginosa from gastrointestinal tract, we investigated the anti-adherence and gut microbiota modulation properties of marine prebiotic fucoidans. METHODS: Proteomic analysis of culture supernatant was performed by LC-MS/MS. Using lectin-based enzyme-linked immunosorbent assay, hemagglutinin domain interaction and inhibition with biomolecules were studied. We investigated the role of nutritional grade fucoidans in a mouse model and used 16S ribosomal RNA sequencing to examine fecal microbiota composition. RESULTS: Analysis of culture supernatant proteins indicated the secretion of two-partner secretion (TPS) family proteins, including TpsA1/CdiA2 and TpsA2/CdiA1. Lectin like activity at the N-terminal of TpsA due to a conserved hemagglutinin domain (Pfam identifier [ID] PF05860) mediates binding to mucins that carry multiple fucosylated glycans. Fucose-rich sulfated polysaccharides (fucoidans) and sulfated dextrans were found to be potent inhibitors of the recombinant N-terminal hemagglutinin domain of TpsA (TpsA-NT-HAD) binding to mucins. In a mouse model, antibiotic-induced dysbiosis was essential for P. aeruginosa gastrointestinal colonization. After prophylactic oral fucoidans supplementation, a higher proportion (60%) of the mice were decolonized over time and resisted re-colonization, this was associated with remarkable expansion of Bacteroides (post-infection day-3 abundance, 29-50%) and consequential reductions in bloom of Enterobacteriaceae and Enterococcaceae populations. In the non-supplemented group, Parabacteroides mediated recovery from dysbiosis but failed to decolonize P. aeruginosa. CONCLUSIONS: Supplementing diet with marine prebiotic fucoidans can mediate earlier recovery from dysbiosis and decolonization of P. aeruginosa from gut by inhibiting secreted virulence factor (TpsA/CdiA) interaction with mucins and promoting the growth of beneficial Bacteroides population. We suggest the prophylactic use of nutritional grade fucoidans to decolonize P. aeruginosa from gastrointestinal tract of at-risk individuals to prevent infection and transmission of colonizing P. aeruginosa.

Gut mycobiome dysbiosis and its impact on intestinal permeability in attention-deficit/hyperactivity disorder.

BACKGROUND: Dysbiosis in the gut microbial community might be involved in the pathophysiology of attention-deficit/hyperactivity disorder (ADHD). The fungal component of the gut microbiome, namely the mycobiota, is a hyperdiverse group of multicellular eukaryotes that can influence host intestinal permeability. This study therefore aimed to investigate the impact of fungal mycobiome dysbiosis and intestinal permeability on ADHD. METHODS: Faecal samples were collected from 35 children with ADHD and from 35 healthy controls. Total DNA was extracted from the faecal samples and the internal transcribed spacer regions were sequenced using high-throughput next-generation sequencing (NGS). The fungal taxonomic classification was analysed using bioinformatics tools and the differentially expressed fungal species between the ADHD and healthy control groups were identified. An in vitro permeability assay (Caco-2 cell layer) was used to evaluate the biological effects of fungal dysbiosis on intestinal epithelial barrier function. RESULTS: The ß-diversity (the species diversity between two communities), but not α-diversity (the species diversity within a community), reflected the differences in fungal community composition between ADHD and control groups. At the phylum level, the ADHD group displayed a significantly higher abundance of Ascomycota and a significantly lower abundance of Basidiomycota than the healthy control group. At the genus level, the abundance of Candida (especially Candida albicans) was significantly increased in ADHD patients compared to the healthy controls. In addition, the in vitro cell assay revealed that C. albicans secretions significantly enhanced the permeability of Caco-2 cells. CONCLUSIONS: The current study is the first to explore altered gut mycobiome dysbiosis using the NGS platform in ADHD. The findings from this study indicated that dysbiosis of the fungal mycobiome and intestinal permeability might be associated with susceptibility to ADHD.

Association of exacerbation phenotype with the sputum microbiome in chronic obstructive pulmonary disease patients during the clinically stable state.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a progressive, life-threatening lung disease with increasing prevalence and incidence worldwide. Increasing evidence suggests that lung microbiomes might play a physiological role in acute exacerbations of COPD. The objective of this study was to characterize the association of the microbiota and exacerbation risk or airflow limitation in stable COPD patients. METHODS: The sputum microbiota from 78 COPD outpatients during periods of clinical stability was investigated using 16S rRNA V3-V4 amplicon sequencing. The microbiome profiles were compared between patients with different risks of exacerbation, i.e., the low risk exacerbator (LRE) or high risk exacerbator (HRE) groups, and with different airflow limitation severity, i.e., mild to moderate (FEV1 ≥ 50; PFT I) or severe to very severe (FEV1 < 50; PFT II). RESULTS: The bacterial diversity (Chao1 and observed OTUs) was significantly decreased in the HRE group compared to that in the LRE group. The top 3 dominant phyla in sputum were Firmicutes, Actinobacteria, and Proteobacteria, which were similar in the HRE and LRE groups. At the genus level, compared to that in the LRE group (41.24%), the proportion of Streptococcus was slightly decreased in the HRE group (28.68%) (p = 0.007). However, the bacterial diversity and the proportion of dominant bacteria at the phylum and genus levels were similar between the PFT I and PFT II groups. Furthermore, the relative abundances of Gemella morbillorum, Prevotella histicola, and Streptococcus gordonii were decreased in the HRE group compared to those in the LRE group according to linear discriminant analysis effect size (LEfSe). Microbiome network analysis suggested altered bacterial cooperative regulation in different exacerbation phenotypes. The proportions of Proteobacteria and Neisseria were negatively correlated with the FEV1/FVC value. According to functional prediction of sputum bacterial communities through Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) analysis, genes involved in lipopolysaccharide biosynthesis and energy metabolism were enriched in the HRE group. CONCLUSION: The present study revealed that the sputum microbiome changed in COPD patients with different risks of exacerbation. Additionally, the bacterial cooperative networks were altered in the HRE patients and may contribute to disease exacerbation. Our results provide evidence that sputum microbiome community dysbiosis is associated with different COPD phenotypes, and we hope that by understanding the lung microbiome, a potentially modifiable clinical factor, further targets for improved COPD therapies during the clinically stable state may be elucidated.

mSignatureDB: a database for deciphering mutational signatures in human cancers.

Cancer is a genetic disease caused by somatic mutations; however, the understanding of the causative biological processes generating these mutations is limited. A cancer genome bears the cumulative effects of mutational processes during tumor development. Deciphering mutational signatures in cancer is a new topic in cancer research. The Wellcome Trust Sanger Institute (WTSI) has categorized 30 reference signatures in the COSMIC database based on the analyses of ∼10 000 sequencing datasets from TCGA and ICGC. Large cohorts and bioinformatics skills are required to perform the same analysis as WTSI. The quantification of known signatures in custom cohorts is not possible under the current framework of the COSMIC database, which motivates us to construct a database for mutational signatures in cancers and make such analyses more accessible to general researchers. mSignatureDB (http://tardis.cgu.edu.tw/msignaturedb) integrates R packages and in-house scripts to determine the contributions of the published signatures in 15 780 individual tumors from 73 TCGA/ICGC cancer projects, making comparison of signature patterns within and between projects become possible. mSignatureDB also allows users to perform signature analysis on their own datasets, quantifying contributions of signatures at sample resolution, which is a unique feature of mSignatureDB not available in other related databases.

Gut microbiota and dietary patterns in children with attention-deficit/hyperactivity disorder.

Attention-deficit/hyperactivity disorder (ADHD) is a common neurodevelopmental disorder, but the underlying pathophysiological mechanisms of ADHD remain unclear. Gut microbiota has been recognized to influence brain function and behaviors. Therefore, this study aimed to determine whether imbalanced gut microbiomes identified by a 16S rRNA sequencing approach are involved in the pathophysiology of ADHD. We recruited a total of 30 children with ADHD (mean age: 8.4 years) and a total of 30 healthy controls (mean age: 9.3 years) for this study. The dietary patterns of all participants were assessed with the food frequency questionnaire. The microbiota of fecal samples were investigated using 16S rRNA V3V4 amplicon sequencing, followed by bioinformatics and statistical analyses. We found that the gut microbiota communities in ADHD patients showed a significantly higher Shannon index and Chao index than the control subjects. Furthermore, the linear discriminant analysis effect size (LEfSe) analysis was used to identify differentially enriched bacteria between ADHD patients and healthy controls. The relative abundance of Bacteroides coprocola (B. coprocola) was decreased, while the relative abundance of Bacteroides uniformis (B. uniformis), Bacteroides ovatus (B. ovatus), and Sutterella stercoricanis (S. stercoricanis) were increased in the ADHD group. Of all participants, S. stercoricanis demonstrated a significant association with the intake of dairy, nuts/seeds/legumes, ferritin and magnesium. B. ovatus and S. stercoricanis were positively correlated to ADHD symptoms. In conclusion, we suggest that the gut microbiome community is associated with dietary patterns, and linked to the susceptibility to ADHD.

Pathogenic Protist Transmembranome database (PPTdb): a web-based platform for searching and analysis of protist transmembrane proteins.

BACKGROUND: Pathogenic protist membrane transporter proteins play important roles not only in exchanging molecules into and out of cells but also in acquiring nutrients and biosynthetic compounds from their hosts. Currently, there is no centralized protist membrane transporter database published, which makes system-wide comparisons and studies of host-pathogen membranomes difficult to achieve. RESULTS: We analyzed over one million protein sequences from 139 protists with full or partial genome sequences. Putative transmembrane proteins were annotated by primary sequence alignments, conserved secondary structural elements, and functional domains. We have constructed the PPTdb (Pathogenic Protist Transmembranome database), a comprehensive membrane transporter protein portal for pathogenic protists and their human hosts. The PPTdb is a web-based database with a user-friendly searching and data querying interface, including hierarchical transporter classification (TC) numbers, protein sequences, functional annotations, conserved functional domains, batch sequence retrieving and downloads. The PPTdb also serves as an analytical platform to provide useful comparison/mining tools, including transmembrane ability evaluation, annotation of unknown proteins, informative visualization charts, and iterative functional mining of host-pathogen transporter proteins. CONCLUSIONS: The PPTdb collected putative protist transporter proteins and offers a user-friendly data retrieving interface. Moreover, a pairwise functional comparison ability can provide useful information for identifying functional uniqueness of each protist. Finally, the host and non-host protein similarity search can fulfill the needs of comprehensive studies of protists and their hosts. The PPTdb is freely accessible at http://pptdb.cgu.edu.tw .

VAReporter: variant reporter for cancer research of massive parallel sequencing.

BACKGROUND: High throughput sequencing technologies have been an increasingly critical aspect of precision medicine owing to a better identification of disease targets, which contributes to improved health care cost and clinical outcomes. In particular, disease-oriented targeted enrichment sequencing is becoming a widely-accepted application for diagnostic purposes, which can interrogate known diagnostic variants as well as identify novel biomarkers from panels of entire human coding exome or disease-associated genes. RESULTS: We introduce a workflow named VAReporter to facilitate the management of variant assessment in disease-targeted sequencing, the identification of pathogenic variants, the interpretation of biological effects and the prioritization of clinically actionable targets. State-of-art algorithms that account for mutation phenotypes are used to rank the importance of mutated genes through visual analytic strategies. We established an extensive annotation source by integrating a wide variety of biomedical databases and followed the American College of Medical Genetics and Genomics (ACMG) guidelines for interpretation and reporting of sequence variations. CONCLUSIONS: In summary, VAReporter is the first web server designed to provide a "one-stop" resource for individual's diagnosis and large-scale cohort studies, and is freely available at http://rnd.cgu.edu.tw/vareporter .

CMPD: cancer mutant proteome database.

Whole-exome sequencing, which centres on the protein coding regions of disease/cancer associated genes, represents the most cost-effective method to-date for deciphering the association between genetic alterations and diseases. Large-scale whole exome/genome sequencing projects have been launched by various institutions, such as NCI, Broad Institute and TCGA, to provide a comprehensive catalogue of coding variants in diverse tissue samples and cell lines. Further functional and clinical interrogation of these sequence variations must rely on extensive cross-platforms integration of sequencing information and a proteome database that explicitly and comprehensively archives the corresponding mutated peptide sequences. While such data resource is a critical for the mass spectrometry-based proteomic analysis of exomic variants, no database is currently available for the collection of mutant protein sequences that correspond to recent large-scale genomic data. To address this issue and serve as bridge to integrate genomic and proteomics datasets, CMPD (http://cgbc.cgu.edu.tw/cmpd) collected over 2 millions genetic alterations, which not only facilitates the confirmation and examination of potential cancer biomarkers but also provides an invaluable resource for translational medicine research and opportunities to identify mutated proteins encoded by mutated genes.

PARRoT- a homology-based strategy to quantify and compare RNA-sequencing from non-model organisms.

BACKGROUND: Next-generation sequencing promises the de novo genomic and transcriptomic analysis of samples of interests. However, there are only a few organisms having reference genomic sequences and even fewer having well-defined or curated annotations. For transcriptome studies focusing on organisms lacking proper reference genomes, the common strategy is de novo assembly followed by functional annotation. However, things become even more complicated when multiple transcriptomes are compared. RESULTS: Here, we propose a new analysis strategy and quantification methods for quantifying expression level which not only generate a virtual reference from sequencing data, but also provide comparisons between transcriptomes. First, all reads from the transcriptome datasets are pooled together for de novo assembly. The assembled contigs are searched against NCBI NR databases to find potential homolog sequences. Based on the searched result, a set of virtual transcripts are generated and served as a reference transcriptome. By using the same reference, normalized quantification values including RC (read counts), eRPKM (estimated RPKM) and eTPM (estimated TPM) can be obtained that are comparable across transcriptome datasets. In order to demonstrate the feasibility of our strategy, we implement it in the web service PARRoT. PARRoT stands for Pipeline for Analyzing RNA Reads of Transcriptomes. It analyzes gene expression profiles for two transcriptome sequencing datasets. For better understanding of the biological meaning from the comparison among transcriptomes, PARRoT further provides linkage between these virtual transcripts and their potential function through showing best hits in SwissProt, NR database, assigning GO terms. Our demo datasets showed that PARRoT can analyze two paired-end transcriptomic datasets of approximately 100 million reads within just three hours. CONCLUSIONS: In this study, we proposed and implemented a strategy to analyze transcriptomes from non-reference organisms which offers the opportunity to quantify and compare transcriptome profiles through a homolog based virtual transcriptome reference. By using the homolog based reference, our strategy effectively avoids the problems that may cause from inconsistencies among transcriptomes. This strategy will shed lights on the field of comparative genomics for non-model organism. We have implemented PARRoT as a web service which is freely available at http://parrot.cgu.edu.tw .

Vanno: a visualization-aided variant annotation tool.

Next-generation sequencing (NGS) technologies have revolutionized the field of genetics and are trending toward clinical diagnostics. Exome and targeted sequencing in a disease context represent a major NGS clinical application, considering its utility and cost-effectiveness. With the ongoing discovery of disease-associated genes, various gene panels have been launched for both basic research and diagnostic tests. However, the fundamental inconsistencies among the diverse annotation sources, software packages, and data formats have complicated the subsequent analysis. To manage disease-associated NGS data, we developed Vanno, a Web-based application for in-depth analysis and rapid evaluation of disease-causative genome sequence alterations. Vanno integrates information from biomedical databases, functional predictions from available evaluation models, and mutation landscapes from TCGA cancer types. A highly integrated framework that incorporates filtering, sorting, clustering, and visual analytic modules is provided to facilitate exploration of oncogenomics datasets at different levels, such as gene, variant, protein domain, or three-dimensional structure. Such design is crucial for the extraction of knowledge from sequence alterations and translating biological insights into clinical applications. Taken together, Vanno supports almost all disease-associated gene tests and exome sequencing panels designed for NGS, providing a complete solution for targeted and exome sequencing analysis. Vanno is freely available at http://cgts.cgu.edu.tw/vanno.

Proteomic analyses of genes regulated by heterogeneous nuclear ribonucleoproteins A/B in Jurkat cells.

Several lines of evidence suggest that hnRNPs A/B (hnRNPs A1, A2/B1, and A3) play an important role in proliferation, although the functional overlap among members of hnRNPs A/B remains largely unknown. In this study, we have employed RNAi knockdown and proteomic approaches to investigate the biological functions of hnRNPs A/B. Depletion of hnRNP A2, but not A1 or A3, produced a significant inhibition of cellular proliferation in Jurkat cells. Analysis of the proteomes in the cells depleted for hnRNP A1, A2, or A3 has identified a total of 167 differentially expressed proteins in the depleted cells. Network analysis of the proteins altered in the cells depleted for hnRNP A2 revealed that the biological processes likely affected by these proteins are related to cell cycle, cytoskeleton rearrangement, and transcription regulation. Indeed, we have confirmed that the level of RhoA and CrkL was selectively reduced in the cells depleted of hnRNP A2, but not in the cells depleted for hnRNP A1 or A3. Therefore, we suggest that the reduced proliferation observed in the cells depleted of hnRNP A2 may result from its effects on cell adhesion processes in the Jurkat cells.

ProFun: A web server for functional enrichment analysis of parasitic protozoan genes.

BACKGROUND: The initial step to interpreting putative biological functions from comparative multi-omics studies usually starts from a differential expressed gene list followed by functional enrichment analysis (FEA). However, most FEA packages are designed exclusively for humans and model organisms. Although parasitic protozoan is the most important pathogen in the tropics, no FEA package is available for protozoan functional (ProFun) enrichment analysis. To speed up comparative multi-omics research on parasitic protozoans, we constructed ProFun, a web-based, user-friendly platform for the research community. METHODS: ProFun utilizes the Docker container, ShinyProxy, and R Shiny to construct a scalable web service with load-balancing infrastructure. We have integrated a series of visual analytic functions, in-house scripts, and custom-made annotation packages to create three analytical modules for 40 protozoan species: (1) Gene Overlaps; (2) Over-representation Analysis (ORA); (3) Gene Set Enrichment Analysis (GSEA). RESULTS: We have established ProFun, a web server for functional enrichment analysis of differentially expressed genes. FEA becomes as simple as pasting a list of gene IDs into the textbox of our website. Users can customize enrichment parameters and results with just one click. The intuitive web interface and publication-ready charts enable users to reveal meaningful biological events and pinpoint potential targets for further studies. CONCLUSION: ProFun is the first web application that enables gene functional enrichment analysis of parasitic protozoans. In addition to supporting FEA analysis, ProFun also allows the comparison of FEA results across complicated experimental designs. ProFun is freely available at http://dalek.cgu.edu.tw:8080/app/profun.

Microbiome of limb-threatening diabetic foot ulcers indicates the association of fastidious Stenotrophomonas and major amputation.

BACKGROUND: Proper identification of the polymicrobial microorganisms in patients with limb-threatening diabetic foot ulcers (LTDFUs) using conventional culture is insufficient. This prospective study evaluates the potential value of adjuvant molecular testing assisting in identify fastidious micro-organisms in LTDFUs compared to standard treatment alone. METHODS: Ninety patients with LTDFUs received interdisciplinary and standard antibiotic treatment in a referral diabetic foot center. A simultaneous 16S amplicon sequencing (16S AS) specimen along with conventional culture collected at admission was used to retrospectively evaluate the microbiological findings and its association with amputation outcomes. RESULTS: The microorganism count revealed by 16S AS overwhelmed that of conventional culturing (17 vs. 3 bacteria/ulcer respectively). The Stenotrophomonas spp. revealed in 29 patients were highly correlated with major (above ankle) amputation (OR: 4.76, 95% CI 1.01-22.56), while only one had been concomitantly identified by conventional culturing. Thus, there were 27 cases without proper antibiotics coverage during treatment. CONCLUSIONS: Adjuvant molecular testing assisted identification of fastidious pathogens such as Stenotrophomonas infection and might be associated with major amputation in patients with LTDFUs.

The core exosome proteome of Trichomonas vaginalis.

BACKGROUND: Trichomonas vaginalis is parasitic protozoan that causes human urogenital infections. Accumulated reports indicated that exosomes released by this parasite play a crucial role in transmitting information and substances between cells during host-parasite interactions. Current knowledge on the protein contents in T. vaginalis exosome is mainly generated from three previous studies that used different T. vaginalis isolates as an experimental model. Whether T. vaginalis exosomes comprise a common set of proteins (core exosome proteome) is still unclear. METHODS: To explore the core exosome proteome in T. vaginalis, we used liquid chromatography-tandem mass spectrometry (LC-MS/MS) to identify the contents of sucrose ultracentrifugation-enriched exosome and supernatant fractions isolated from six isolates. RESULTS: Transmission electron microscopy (TEM) confirmed the presence of exosomes in the enriched fraction. Proteomic analysis identified a total of 1870 proteins from exosomal extracts. There were 1207 exosomal-specific proteins after excluding 436 'non-core exosomal proteins'. Among these, 72 common exosomal-specific proteins were expressed in all six isolates. Compared with three published T. vaginalis exosome proteome datasets, we identified 16 core exosomal-specific proteins. These core exosomal-specific proteins included tetraspanin (TvTSP1), the classical exosome marker, and proteins mainly involved in catalytic activity and binding such as ribosomal proteins, ras-associated binding (Rab) proteins, and heterotrimeric G proteins. CONCLUSIONS: Our study highlighted the importance of using supernatant fraction from exosomal extract as a control to eliminate 'non-core exosomal proteins'. We compiled a reference core exosome proteome of T. vaginalis, which is essential for developing a fundamental understanding of exosome-mediated cell communication and host-parasite interaction.

Gut microbiota and clinical response to immune checkpoint inhibitor therapy in patients with advanced cancer.

BACKGROUND: There is currently no well-accepted consensus on the association between gut microbiota and the response to treatment of immune checkpoint inhibitors (ICIs) in patients with advanced cancer. METHODS: Fecal samples were collected before ICI treatment. Gut microbiota was analyzed using 16 S ribosomal RNA sequencing. We investigated the relationship between the α-diversity of fecal microbiota and patients' clinical outcomes. Microbiota profiles from patients and healthy controls were determined. Pre-treatment serum was examined by cytokine array. RESULTS: We analyzed 74 patients, including 42 with melanoma, 8 with kidney cancer, 13 with lung cancer, and 11 with other cancers. Combination therapy of anti-PD1 and anti-CTLA-4 was used in 14 patients, and monotherapy in the rest. Clinical benefit was observed in 35 (47.3 %) cases, including 2 complete responses, 16 partial responses, and 17 stable diseases according to RECIST criteria. No significant difference in α-diversity was found between the benefiter and non-benefiter groups. However, patients with α-diversity within the range of our healthy control had a significantly longer median overall survival (18.9 months), compared to the abnormal group (8.2 months) (p = 0.041, hazard ratio = 0.546) for all patients. The microbiota composition of the benefiters was similar to that of healthy individuals. Furthermore, specific bacteria, such as Prevotella copri and Faecalibacterium prausnitzii, were associated with a favorable outcome. We also observed that serum IL-18 before treatment was significantly lower in the benefiters, compared to non-benefiters. CONCLUSIONS: The α-diversity of gut microbiota is positively correlated with more prolonged overall survival in cancer patients following ICI therapy.

CPAP: Cancer Panel Analysis Pipeline.

Targeted sequencing using next-generation sequencing technologies is currently being rapidly adopted for clinical sequencing and cancer marker tests. However, no existing bioinformatics tool is available for the analysis and visualization of multiple targeted sequencing datasets. In the present study, we use cancer panel targeted sequencing datasets generated by the Life Technologies Ion Personal Genome Machine Sequencer as an example to illustrate how to develop an automated pipeline for the comparative analyses of multiple datasets. Cancer Panel Analysis Pipeline (CPAP) uses standard output files from variant calling software to generate a distribution map of SNPs among all of the samples in a circular diagram generated by Circos. The diagram is hyperlinked to a dynamic HTML table that allows the users to identify target SNPs by using different filters. CPAP also integrates additional information about the identified SNPs by linking to an integrated SQL database compiled from SNP-related databases, including dbSNP, 1000 Genomes Project, COSMIC, and dbNSFP. CPAP only takes 17 min to complete a comparative analysis of 500 datasets. CPAP not only provides an automated platform for the analysis of multiple cancer panel datasets but can also serve as a model for any customized targeted sequencing project.