Genome-wide DNA methylation changes in human spermatogenesis.

Sperm production and function require the correct establishment of DNA methylation patterns in the germline. Here, we examined the genome-wide DNA methylation changes during human spermatogenesis and its alterations in disturbed spermatogenesis. We found that spermatogenesis is associated with remodeling of the methylome, comprising a global decline in DNA methylation in primary spermatocytes followed by selective remethylation, resulting in a spermatids/sperm-specific methylome. Hypomethylated regions in spermatids/sperm were enriched in specific transcription factor binding sites for DMRT and SOX family members and spermatid-specific genes. Intriguingly, while SINEs displayed differential methylation throughout spermatogenesis, LINEs appeared to be protected from changes in DNA methylation. In disturbed spermatogenesis, germ cells exhibited considerable DNA methylation changes, which were significantly enriched at transposable elements and genes involved in spermatogenesis. We detected hypomethylation in SVA and L1HS in disturbed spermatogenesis, suggesting an association between the abnormal programming of these regions and failure of germ cells progressing beyond meiosis.

Early blast clearance during sequential conditioning prior to allogeneic stem cell transplantation in patients with acute myeloid leukaemia.

For patients with relapsed or refractory AML, sequential conditioning prior to allogeneic stem cell transplantation (alloSCT) is an established and potentially curative treatment option. Early response to treatment during conditioning indicates chemotherapy-responsive disease and may have prognostic value. We retrospectively evaluated blast clearance on day 5 after melphalan, administered 11 days prior to alloSCT as part of a sequential conditioning in 176 patients with active AML. Overall survival (OS) was 52% (95% confidence interval [CI] 45%-60%), and relapse-free survival (RFS) was 47% (95% CI 40%-55%) at 3 years. Patients who achieved early blast clearance did not show a significant improvement in OS and RFS (OS, hazard ratio [HR] HR 0.75, p 0.19; RFS, HR 0.71, p 0.09, respectively), but had a significantly lower non-relapse mortality rate (HR 0.46, p 0.017). HLA-mismatched donor, older age, adverse genetic risk and higher comorbidity scores were associated with inferior survival outcomes. A high initial blast count was only associated with inferior prognosis in patients receiving chemotherapy-only compared to total body irradiation containing conditioning therapy. These results indicate that for patients transplanted with active AML, sensitivity to chemotherapy might be of less importance, compared to other disease- and transplant-related factors.

OGRE: calculate, visualize, and analyze overlap between genomic input regions and public annotations.

BACKGROUND: Modern genome sequencing leads to an ever-growing collection of genomic annotations. Combining these elements with a set of input regions (e.g. genes) would yield new insights in genomic associations, such as those involved in gene regulation. The required data are scattered across different databases making a manual approach tiresome, unpractical, and prone to error. Semi-automatic approaches require programming skills in data parsing, processing, overlap calculation, and visualization, which most biomedical researchers lack. Our aim was to develop an automated tool providing all necessary algorithms, benefiting both bioinformaticians and researchers without bioinformatic training. RESULTS: We developed overlapping annotated genomic regions (OGRE) as a comprehensive tool to associate and visualize input regions with genomic annotations. It does so by parsing regions of interest, mining publicly available annotations, and calculating possible overlaps between them. The user can thus identify location, type, and number of associated regulatory elements. Results are presented as easy to understand visualizations and result tables. We applied OGRE to recent studies and could show high reproducibility and potential new insights. To demonstrate OGRE's performance in terms of running time and output, we have conducted a benchmark and compared its features with similar tools. CONCLUSIONS: OGRE's functions and built-in annotations can be applied as a downstream overlap association step, which is compatible with most genomic sequencing outputs, and can thus enrich pre-existing analyses pipelines. Compared to similar tools, OGRE shows competitive performance, offers additional features, and has been successfully applied to two recent studies. Overall, OGRE addresses the lack of tools for automatic analysis, local genomic overlap calculation, and visualization by providing an easy to use, end-to-end solution for both biologists and computational scientists.

Group-specific cellular metabolism in Medulloblastoma.

BACKGROUND: Cancer metabolism influences multiple aspects of tumorigenesis and causes diversity across malignancies. Although comprehensive research has extended our knowledge of molecular subgroups in medulloblastoma (MB), discrete analysis of metabolic heterogeneity is currently lacking. This study seeks to improve our understanding of metabolic phenotypes in MB and their impact on patients' outcomes. METHODS: Data from four independent MB cohorts encompassing 1,288 patients were analysed. We explored metabolic characteristics of 902 patients (ICGC and MAGIC cohorts) on bulk RNA level. Moreover, data from 491 patients (ICGC cohort) were searched for DNA alterations in genes regulating cell metabolism. To determine the role of intratumoral metabolic differences, we examined single-cell RNA-sequencing (scRNA-seq) data from 34 additional patients. Findings on metabolic heterogeneity were correlated to clinical data. RESULTS: Established MB groups exhibit substantial differences in metabolic gene expression. By employing unsupervised analyses, we identified three clusters of group 3 and 4 samples with distinct metabolic features in ICGC and MAGIC cohorts. Analysis of scRNA-seq data confirmed our results of intertumoral heterogeneity underlying the according differences in metabolic gene expression. On DNA level, we discovered clear associations between altered regulatory genes involved in MB development and lipid metabolism. Additionally, we determined the prognostic value of metabolic gene expression in MB and showed that expression of genes involved in metabolism of inositol phosphates and nucleotides correlates with patient survival. CONCLUSION: Our research underlines the biological and clinical relevance of metabolic alterations in MB. Thus, distinct metabolic signatures presented here might be the first step towards future metabolism-targeted therapeutic options.

Integrative genomic analysis of pediatric T-cell lymphoblastic lymphoma reveals candidates of clinical significance.

T-cell lymphoblastic lymphoma (T-LBL) is a heterogeneous malignancy of lymphoblasts committed to T-cell lineage. The dismal outcomes (15%-30%) after T-LBL relapse warrant establishing risk-based treatment. To our knowledge, this study presents the first comprehensive, systematic, integrated, genome-wide analysis including relapsed cases that identifies molecular markers of prognostic relevance for T-LBL. NOTCH1 was identified as the putative driver for T-LBL. An activated NOTCH/PI3K-AKT signaling axis and alterations in cell cycle regulators constitute the core oncogenic program for T-LBL. Mutated KMT2D was identified as a prognostic marker. The cumulative incidence of relapse was 47% ± 17% in patients with KMT2D mutations, compared with 14% ± 3% in wild-type KMT2D. Structural analysis of the mutated domains of KMT2D revealed a plausible impact on structure and functional consequences. These findings provide new insights into the pathogenesis of T-LBL, including high translational potential. The ongoing LBL 2018 trial (www.clinicaltrials.gov #NCT04043494) allows for prospective validation and subsequent fine tuning of the stratification criteria for T-LBL risk groups to improve survival of pediatric patients.

Research article network analysis of polymicrobial chronic wound infections in Masanga, Sierra Leone.

BACKGROUND: Chronic wounds are frequently colonized or infected with multiple bacterial or fungal species, which can both promote or inhibit each other. Network analyses are helpful to understand the interplay of these species in polymicrobial infections. Our aim was to analyse the network of bacterial and fungal species in chronic wounds. METHODS: Swabs (n = 163) from chronic wound infections (Masanga, Sierra Leone, 2019-2020) were screened for bacterial and fungal species using non-selective agars. Some of these wounds were suspected but not confirmed Buruli ulcer. Species identification was done with MALDI-TOF mass spectrometry. Network analysis was performed to investigate co-occurrence of different species within one patient. All species with n ≥ 10 isolates were taken into account. RESULTS: Of the 163 patients, 156 had a positive wound culture (median of three different species per patient; range 1-7). Pseudomonas aeruginosa (n = 75) was the dominating species with frequent co-detections of Klebsiella pneumoniae (21 cases; OR = 1.36, 95%CI: 0.63-2.96, p = 0.47), Staphylococcus aureus (14 cases; OR = 1.06, 95%CI: 0.44-2.55, p = 1) and Proteus mirabilis (13 cases; OR = 0.84, 95%CI: 0.35-1.99, p = 0.69). CONCLUSION: The culturome of chronic wounds in Sierra Leonean patients is highly diverse and characterized by the co-occurrence of P. aeruginosa, K. pneumoniae and S. aureus.

Knockout of the Cardiac Transcription Factor NKX2-5 Results in Stem Cell-Derived Cardiac Cells with Typical Purkinje Cell-like Signal Transduction and Extracellular Matrix Formation.

The human heart controls blood flow, and therewith enables the adequate supply of oxygen and nutrients to the body. The correct function of the heart is coordinated by the interplay of different cardiac cell types. Thereby, one can distinguish between cells of the working myocardium, the pace-making cells in the sinoatrial node (SAN) and the conduction system cells in the AV-node, the His-bundle or the Purkinje fibres. Tissue-engineering approaches aim to generate hiPSC-derived cardiac tissues for disease modelling and therapeutic usage with a significant improvement in the differentiation quality of myocardium and pace-making cells. The differentiation of cells with cardiac conduction system properties is still challenging, and the produced cell mass and quality is poor. Here, we describe the generation of cardiac cells with properties of the cardiac conduction system, called conduction system-like cells (CSLC). As a primary approach, we introduced a CrispR-Cas9-directed knockout of the NKX2-5 gene in hiPSC. NKX2-5-deficient hiPSC showed altered connexin expression patterns characteristic for the cardiac conduction system with strong connexin 40 and connexin 43 expression and suppressed connexin 45 expression. Application of differentiation protocols for ventricular- or SAN-like cells could not reverse this connexin expression pattern, indicating a stable regulation by NKX2-5 on connexin expression. The contraction behaviour of the hiPSC-derived CSLCs was compared to hiPSC-derived ventricular- and SAN-like cells. We found that the contraction speed of CSLCs resembled the expected contraction rate of human conduction system cells. Overall contraction was reduced in differentiated cells derived from NKX2-5 knockout hiPSC. Comparative transcriptomic data suggest a specification of the cardiac subtype of CSLC that is distinctly different from ventricular or pacemaker-like cells with reduced myocardial gene expression and enhanced extracellular matrix formation for improved electrical insulation. In summary, knockout of NKX2-5 in hiPSC leads to enhanced differentiation of cells with cardiac conduction system features, including connexin expression and contraction behaviour.

Design of a targeted next-generation DNA sequencing panel for pediatric T-cell lymphoblastic lymphoma to unravel biology and optimize treatment.

Low incidence and molecular heterogeneity of pediatric T-cell lymphoblastic lymphoma (T-LBL) require an international, large-scale effort to identify novel clinical biomarkers. The ongoing international clinical trial LBL2018 (NCT04043494) represents an ideal opportunity to implement a common analytic approach. Targeted next-generation sequencing is well-suited for this purpose; however, selection of relevant target genes for T-LBL remains subject of ongoing debates. Our group has recently designed and evaluated a first target panel of 80 candidate genes for T-LBL. The present study aimed at developing a novel optimized gene panel for large-scale application and to promote an international agreement on a common core panel. Small sequence variants obtained from our former study were systematically analyzed and classified with regards to pathogenic relevance, to prioritize candidate genes. Additional genes were curated from literature and online databases for a more comprehensive analysis of relevant functions and signaling pathways. The new target panel TGP-T-LBL entails 84 candidate genes which are key actors in NOTCH, PI3K-AKT, JAK-STAT, RAS signaling, epigenetic regulation, transcription, DNA repair, cell cycle regulation, and ribosomal function. From our former gene panel, 35 out of 80 candidate genes were selected for the novel panel. Forty-six out of 84 genes are currently being analyzed in the ongoing international trial LBL2018. Exploratory analysis of prognostic relevance on mutation-level suggested a potential association of PIK3CA variants c.1624G>A(p.Glu542Lys) and c.1633G>A(p.Glu545Lys) to occurrence of relapse, emphasizing particular relevance of mutation analysis in PI3K-AKT signaling. Our approach promotes comprehensive and clinically relevant mutational profiling of pediatric T-LBL.

appreci8: a pipeline for precise variant calling integrating 8 tools.

Motivation: The application of next-generation sequencing in research and particularly in clinical routine requires valid variant calling results. However, evaluation of several commonly used tools has pointed out that not a single tool meets this requirement. False positive as well as false negative calls necessitate additional experiments and extensive manual work. Intelligent combination and output filtration of different tools could significantly improve the current situation. Results: We developed appreci8, an automatic variant calling pipeline for calling single nucleotide variants and short indels by combining and filtering the output of eight open-source variant calling tools, based on a novel artifact- and polymorphism score. Appreci8 was trained on two data sets from patients with myelodysplastic syndrome, covering 165 Illumina samples. Subsequently, appreci8's performance was tested on five independent data sets, covering 513 samples. Variation in sequencing platform, target region and disease entity was considered. All calls were validated by re-sequencing on the same platform, a different platform or expert-based review. Sensitivity of appreci8 ranged between 0.93 and 1.00, while positive predictive value ranged between 0.65 and 1.00. In all cases, appreci8 showed superior performance compared to any evaluated alternative approach. Availability and implementation: Appreci8 is freely available at https://hub.docker.com/r/wwuimi/appreci8/. Sequencing data (BAM files) of the 678 patients analyzed with appreci8 have been deposited into the NCBI Sequence Read Archive (BioProjectID: 388411; https://www.ncbi.nlm.nih.gov/bioproject/PRJNA388411). Supplementary information: Supplementary data are available at Bioinformatics online.

Sperm size is negatively related to relative testis size in West African riverine cichlid fishes.

Fishes show a great diversity of mating systems and fertilization mechanisms. This diversity creates an enormous potential for sperm competition. Typically, monogamous species face a low risk of sperm competition and invest less into sperm, and thus show smaller relative testis mass compared to polygamous species with high sperm competition. In cichlids, sperm competition risk is very variable. In lacustrine East African cichlids, large sperm are interpreted as an adaptation to sperm competition, as in those species sperm length correlates with sperm swimming speed. The aim of the present study was to examine variation in sperm and testis traits of substrate breeding cichlids from West African river systems and its relationship to sperm competition. Therefore, sperm traits (total sperm size, flagellum-, midpiece-, and head size) and sperm number were related to the gonadosomatic index (GSI), an indicator of sperm competition, in eight species of two large informal tribes, the chromidotilapiines and the haplotilapiines. We found significant differences between species in all examined sperm traits, sperm number, and GSI with pronounced differences between chromidotilapiines and haplotilapiines. We used a generalized least-squares approach to control for non-independence of data. GSI was positively correlated with sperm number but negatively correlated with total sperm size (also negatively with the flagellum and head size but not significantly with midpiece size). Sperm number and sperm size were negatively correlated suggesting a trade-off between sperm size and quality. Our results suggest that large sperm can evolve in species with relatively low sperm expenditure and probably in absence of high sperm competition between males.

Web-Based Information Infrastructure Increases the Interrater Reliability of Medical Coders: Quasi-Experimental Study.

BACKGROUND: Medical coding is essential for standardized communication and integration of clinical data. The Unified Medical Language System by the National Library of Medicine is the largest clinical terminology system for medical coders and Natural Language Processing tools. However, the abundance of ambiguous codes leads to low rates of uniform coding among different coders. OBJECTIVE: The objective of our study was to measure uniform coding among different medical experts in terms of interrater reliability and analyze the effect on interrater reliability using an expert- and Web-based code suggestion system. METHODS: We conducted a quasi-experimental study in which 6 medical experts coded 602 medical items from structured quality assurance forms or free-text eligibility criteria of 20 different clinical trials. The medical item content was selected on the basis of mortality-leading diseases according to World Health Organization data. The intervention comprised using a semiautomatic code suggestion tool that is linked to a European information infrastructure providing a large medical text corpus of >300,000 medical form items with expert-assigned semantic codes. Krippendorff alpha (Kalpha) with bootstrap analysis was used for the interrater reliability analysis, and coding times were measured before and after the intervention. RESULTS: The intervention improved interrater reliability in structured quality assurance form items (from Kalpha=0.50, 95% CI 0.43-0.57 to Kalpha=0.62 95% CI 0.55-0.69) and free-text eligibility criteria (from Kalpha=0.19, 95% CI 0.14-0.24 to Kalpha=0.43, 95% CI 0.37-0.50) while preserving or slightly reducing the mean coding time per item for all 6 coders. Regardless of the intervention, precoordination and structured items were associated with significantly high interrater reliability, but the proportion of items that were precoordinated significantly increased after intervention (eligibility criteria: OR 4.92, 95% CI 2.78-8.72; quality assurance: OR 1.96, 95% CI 1.19-3.25). CONCLUSIONS: The Web-based code suggestion mechanism improved interrater reliability toward moderate or even substantial intercoder agreement. Precoordination and the use of structured versus free-text data elements are key drivers of higher interrater reliability.

BBCAnalyzer: a visual approach to facilitate variant calling.

BACKGROUND: Deriving valid variant calling results from raw next-generation sequencing data is a particularly challenging task, especially with respect to clinical diagnostics and personalized medicine. However, when using classic variant calling software, the user usually obtains nothing more than a list of variants that pass the corresponding caller's internal filters. Any expected mutations (e.g. hotspot mutations), that have not been called by the software, need to be investigated manually. RESULTS: BBCAnalyzer (Bases By CIGAR Analyzer) provides a novel visual approach to facilitate this step of time-consuming, manual inspection of common mutation sites. BBCAnalyzer is able to visualize base counts at predefined positions or regions in any sequence alignment data that are available as BAM files. Thereby, the tool provides a straightforward solution for evaluating any list of expected mutations like hotspot mutations, or even whole regions of interest. In addition to an ordinary textual report, BBCAnalyzer reports highly customizable plots. Information on the counted number of bases, the reference bases, known mutations or polymorphisms, called mutations and base qualities is summarized in a single plot. By uniting this information in a graphical way, the user may easily decide on a variant being present or not - completely independent of any internal filters or frequency thresholds. CONCLUSIONS: BBCAnalyzer provides a unique, novel approach to facilitate variant calling where classical tools frequently fail to call. The R package is freely available at http://bioconductor.org . The local web application is available at Additional file 2. A documentation of the R package (Additional file 1) as well as the web application (Additional file 2) with detailed descriptions, examples of all input- and output elements, exemplary code as well as exemplary data are included. A video demonstrates the exemplary usage of the local web application (Additional file 3). Additional file 3: Supplement_3. Video demonstrating the exemplary usage of the web application "BBCAnalyzer". (MP4 11571 kb).

Childhood coeliac disease: diagnostic pathways update.

The modification of European guidelines now enables coeliac disease to be diagnosed without a small-bowel biopsy in a selective group of symptomatic children. The recommendations have been adopted by the Coeliac UK and the British Society of Paediatric Gastroenterology, Hepatology and Nutrition. As well as highlighting how health professionals can help identify coeliac disease at an earlier stage, this article details the amendments to the guidance and the diagnostic pathways that should be followed.

Systematic analysis of ChatGPT, Google search and Llama 2 for clinical decision support tasks.

It is likely that individuals are turning to Large Language Models (LLMs) to seek health advice, much like searching for diagnoses on Google. We evaluate clinical accuracy of GPT-3·5 and GPT-4 for suggesting initial diagnosis, examination steps and treatment of 110 medical cases across diverse clinical disciplines. Moreover, two model configurations of the Llama 2 open source LLMs are assessed in a sub-study. For benchmarking the diagnostic task, we conduct a naïve Google search for comparison. Overall, GPT-4 performed best with superior performances over GPT-3·5 considering diagnosis and examination and superior performance over Google for diagnosis. Except for treatment, better performance on frequent vs rare diseases is evident for all three approaches. The sub-study indicates slightly lower performances for Llama models. In conclusion, the commercial LLMs show growing potential for medical question answering in two successive major releases. However, some weaknesses underscore the need for robust and regulated AI models in health care. Open source LLMs can be a viable option to address specific needs regarding data privacy and transparency of training.

Lack of SMARCB1 expression characterizes a subset of human and murine peripheral T-cell lymphomas.

Peripheral T-cell lymphoma, not otherwise specified (PTCL-NOS) is a heterogeneous group of malignancies with poor outcome. Here, we identify a subgroup, PTCL-NOSSMARCB1-, which is characterized by the lack of the SMARCB1 protein and occurs more frequently in young patients. Human and murine PTCL-NOSSMARCB1- show similar DNA methylation profiles, with hypermethylation of T-cell-related genes and hypomethylation of genes involved in myeloid development. Single-cell analyses of human and murine tumors revealed a rich and complex network of interactions between tumor cells and an immunosuppressive and exhausted tumor microenvironment (TME). In a drug screen, we identified histone deacetylase inhibitors (HDACi) as a class of drugs effective against PTCL-NOSSmarcb1-. In vivo treatment of mouse tumors with SAHA, a pan-HDACi, triggered remodeling of the TME, promoting replenishment of lymphoid compartments and reversal of the exhaustion phenotype. These results provide a rationale for further exploration of HDACi combination therapies targeting PTCL-NOSSMARCB1- within the TME.

GEFAAR: a generic framework for the analysis of antimicrobial resistance providing statistics and cluster analyses.

Easy access to antimicrobial resistance data and meaningful visualization is essential to guide the empirical antimicrobial treatment and to promote the rational use of antimicrobial agents. Currently available solutions are commonly externally hosted, centralized systems. However, there is a need for close monitoring by local analysis tools. To fill this gap, we developed GEFAAR-a generic framework for the analysis of antimicrobial resistance data. Following the example of the German Robert Koch Institute (RKI), an interactive web-application is provided to determine basic pathogen and resistance statistics. In addition to the RKI's externally maintained database, our application provides a generic framework to import tabular data and to analyze them safely in a local environment. Moreover, our application offers an intuitive web-based user interface to visualize resistance trend analysis as well as advanced cluster analyses on species- or clinic/unit level to generate alerts of potential transmission events.

Reconstructing Clonal Evolution-A Systematic Evaluation of Current Bioinformatics Approaches.

The accurate reconstruction of clonal evolution, including the identification of newly developing, highly aggressive subclones, is essential for the application of precision medicine in cancer treatment. Reconstruction, aiming for correct variant clustering and clonal evolution tree reconstruction, is commonly performed by tedious manual work. While there is a plethora of tools to automatically generate reconstruction, their reliability, especially reasons for unreliability, are not systematically assessed. We developed clevRsim-an approach to simulate clonal evolution data, including single-nucleotide variants as well as (overlapping) copy number variants. From this, we generated 88 data sets and performed a systematic evaluation of the tools for the reconstruction of clonal evolution. The results indicate a major negative influence of a high number of clones on both clustering and tree reconstruction. Low coverage as well as an extreme number of time points usually leads to poor clustering results. An underlying branched independent evolution hampers correct tree reconstruction. A further major decline in performance could be observed for large deletions and duplications overlapping single-nucleotide variants. In summary, to explore the full potential of reconstructing clonal evolution, improved algorithms that can properly handle the identified limitations are greatly needed.

Immune gene co-expression signatures implicated in occurence and persistence of cognitive dysfunction in depression.

Cognitive dysfunction contributes significantly to the burden caused by Major Depressive Disorder (MDD). Yet, while compelling evidence suggests that different biological processes play a part in both MDD aetiology and the development of cognitive decline more generally, we only begin to understand the molecular underpinnings of depression-related cognitive impairment. Developments in psychometric assessments, molecular high-throughput methods and systems biology derived analysis strategies advance this endeavour. Here, we aim to identify gene expression signatures associated with cognitive dysfunction and cognitive improvement following therapy using RNA sequencing to analyze the whole blood-derived transcriptome of altogether 101 MDD patients who enrolled in the CERT-D study. The mRNA(Nova)Seq based transcriptome was analyzed from whole blood taken at baseline assessment, and patients' cognitive performance was measured twice at baseline and following eight weeks of therapy by means of the THINC integrated tool. Thirty-six patients showed comparatively low cognitive performance at baseline assessment, and 32 patients showed comparatively strong cognitive improvement following therapy. Differential gene expression analysis was performed using limma to a significance threshold of 0.05 and a logFC cutoff of |1.2|. Although we observed some indications for expression differences related to low cognitive performance and cognitive therapy response, signals did not withstand adjustment for multiple testing. Applying WGCNA, we retrieved altogether 25 modules of co-expressed genes and we used a combination of correlational and linear analyses to identify modules related to baseline cognitive performance and cognitive improvement following therapy. Three immune modules reflected distinct but interrelated immune processes (the yellow module: neutrophil-mediated immunity, the darkorange module: interferon signaling, the tan module: platelet activation), and higher expression of the yellow (r = -0.21, p < .05), the dark orange (r = 0.2, p < .05), and the tan (r = -0.23, p < .05) module correlated significantly negatively with patients' cognitive baseline performance. Patients' cognitive baseline performance was a significant predictor of the darkorange module (b = -0.039, p < .05) and the tan module's expression (b = 0.02, p < .05) and was close to becoming a significant predictor of the yellow module's expression (b = -0.02, p = .05). Furthermore, patients characterized by comparatively low cognitive performance at baseline showed significantly higher expression of the tan module when compared to all other patients F(1,97) = 4.32, p < .05, η= 0.04. Following eight weeks of treatment, we observed altogether significant improvement in patients' cognitive performance (b = 0.30, p < .001), and patients with comparatively high cognitive gain showed noticeably lower, but not significantly lower F(1,98) = 3.76, p = .058, expression of a dark turquoise module, which reflects complement and B-cell-associated immune processes. Noteworthy, the relation between cognitive performance and module expression remained observable after controlling for symptom severity and BMI, which partly accounted for variance in module expression. As such, our findings provide further evidence for the involvement of immune processes in MDD related cognitive dysfunction and they suggest that different immune processes contribute to the development and long-term persistence of cognitive dysfunction in the context of depression.

Pharyngeal Communities and Antimicrobial Resistance in Pangolins in Gabon.

Wildlife can be a reservoir and source of zoonotic pathogens for humans. For instance, pangolins were considered one of the potential animal reservoirs of SARS-CoV-2. The aim of this study was to assess the prevalence of antimicrobial-resistant species (e.g., extended-spectrum ß-lactamase [ESBL]-producing Enterobacterales) and Staphylococcus aureus-related complex and to describe the bacterial community in wild Gabonese pangolins. The pharyngeal colonization of pangolins sold in Gabon (n = 89, 2021 to 2022) was analyzed using culture media selective for ESBL-producing Enterobacterales, S. aureus-related complex, Gram-positive bacteria and nonfermenters. Phylogenetic analyses of ESBL-producing Enterobacterales was done using core-genome multilocus sequence typing (cgMLST) and compared with publicly available genomes. Patterns of cooccurring species were detected by network analysis. Of the 439 bacterial isolates, the majority of species belonged to the genus Pseudomonas (n = 170), followed by Stenotrophomonas (n = 113) and Achromobacter (n = 37). Three Klebsiella pneumoniae isolates and one Escherichia coli isolate were ESBL-producers, which clustered with human isolates from Nigeria (MLST sequence type 1788 [ST1788]) and Gabon (ST38), respectively. Network analysis revealed a frequent cooccurrence of Stenotrophomonas maltophilia with Pseudomonas putida and Pseudomonas aeruginosa. In conclusion, pangolins can be colonized with human-related ESBL-producing K. pneumoniae and E. coli. Unlike in other African wildlife, S. aureus-related complex was not detected in pangolins. IMPORTANCE There is an ongoing debate if pangolins are a relevant reservoir for viruses such as SARS-CoV-2. Here, we wanted to know if African pangolins are colonized with bacteria that are relevant for human health. A wildlife reservoir of antimicrobial resistance would be of medical relevance in regions were consumption of so-called bushmeat is common. In 89 pangolins, we found three ESBL-producing Klebsiella pneumoniae strains and one ESBL-producing Escherichia coli strains, which were closely related to isolates from humans in Africa. This points toward either a transmission between pangolins and humans or a common source from which both humans and pangolins became colonized.