Biology subjects

Dietrich, A.

Publications and source records attributed to Dietrich, A..

At least 19 recordsLinked to original sources

bioRxiv2026

Rectangle: robust and scalable multiscale deconvolution informed by single-cell RNA sequencing data

Bulk RNA-seq enables effective profiling of large cohorts and complex experimental designs, but current single-cell-informed deconvolution methods incompletely resolve closely related cell phenotypes, do not scale efficiently to large single-cell datasets, or fail to account for cellular content not represented in the reference. Here, we present Rectangle, an scverse Python framework for single-cell-informed deconvolution of bulk RNA-seq data. Rectangle combines multiscale deconvolution, capturing cellular composition across multiple resolution levels, with explicit modeling of unknown cellular content. In a diverse, cross-method benchmark, Rectangle achieved consistently strong performance across all evaluated metrics, demonstrating high accuracy, high resolution, low spillover, strong scalability and efficiency, and robustness to unknown cellular content. By bridging the resolution of single-cell transcriptomics with the scale and cost-efficiency of bulk RNA-seq, Rectangle enables cell-type and cell-state profiling at scale, supporting population-scale cellular biomarker discovery and tracking of cellular dynamics in settings impractical for comprehensive single-cell sequencing.

bioinformatics↗

bioRxiv2026

Lipid-mediated regulation of pneumolysin balances vascular injury and bacterial containment during pneumococcal infection

Severe infection with Streptococcus (S.) pneumoniae is a leading cause of acute lung injury, multiorgan failure, and death despite appropriate antibiotic therapy. A major contributor to tissue damage is pneumolysin (PLY), a cholesterol-dependent pore-forming toxin that is released in large amounts during bacterial lysis. Because antibiotic treatment enhances PLY release, understanding the mechanisms that control PLY-induced host injury is critical for the development of strategies that limit tissue damage without impairing antibacterial defense. Using isolated perfused lungs and in situ two-photon imaging, we show that S. pneumoniae induces platelet and leukocyte recruitment, pulmonary edema, perfusion failure, and intravascular bacterial trapping within pulmonary arterioles. These responses required PLY and were associated with endothelial Ca{superscript 2} influx and plasma membrane permeabilization. The oxysterol 25-hydroxycholesterol (25-HC) prevented PLY-dependent Ca{superscript 2} entry, vascular leakage, and perfusion failure by reducing accessible membrane cholesterol through activation of acyl-CoA:cholesterol acyltransferase (ACAT). Unexpectedly, pneumococcal infection suppressed expression of cholesterol-25-hydroxylase (CH25H), the enzyme responsible for 25-HC synthesis, although induction of this pathway would be predicted to protect against toxin-mediated injury. We show that this downregulation results from inhibition of platelet-activating factor (PAF) receptor (PAFR) signaling by pneumococcal phosphocholine-containing cell wall components. Remarkably, both PAF itself and the anti-phosphocholine antibody TEPC directly inhibited PLY pore formation independently of PAFR, while preserving intravascular coagulation and bacterial trapping. Thus, although 25-HC protects against toxin-mediated vascular injury, its suppression may allow coagulation-dependent bacterial containment, with PAF acting as a compensatory antagonist of PLY. These findings identify a lipid-based host defense system in which 25-HC and PAF differentially regulate PLY activity to balance tissue protection with bacterial clearance and suggest new therapeutic approaches to limit the harmful effects of antibiotic-induced PLY release during pneumococcal infection.

immunology↗

bioRxiv2026

Cigarette Smoke Extract (CSE) reduces expression of functional TRPV4 channels in primary human bronchial epithelial cells differentiated at an Air Liquid Interface (ALI) in vitro

Primary human bronchial epithelial cells (pHBECs) of the airways of smokers are chronically exposed to cigarette smoke, which may induce chronic obstructive pulmonary disease (COPD) ranked fourth among the most common global causes of death. Using an established protocol for differentiation of pHBECs to a pseudostratified epithelium at an air liquid interface (ALI), we analyzed functional expression of transient receptor potential vanilloid 4 (TRPV4) proteins after application of cigarette smoke extract (CSE), which upregulated seven smoke exposure regulated genes (SERGs). TRPV4 protein expression in the plasma membrane and localization next to the cilia of ciliated cells was reduced, while cell barrier function was not altered after chronic exposure to CSE for 28 days compared to untreated control cells. Accordingly, TRPV4-mediated Ca2+ influx was blocked in pHBECs after CSE exposure. Moreover, Os-9 protein, which after binding mediates protection from degradation of TRPV4 protein by polyubiquitination, was significantly less expressed in pHBECs upon CSE exposure. Most interestingly, overexpression of OS-9 in pHBECs rescued reduced TRPV4 protein levels induced by CSE. Our study identifies a novel molecular mechanism of toxicity by CSE interfering with TRPV4 and OS-9 expression in pHBECs, which may blaze the trail for new therapeutic options in COPD.

cell biology↗

bioRxiv2026

Brain Age in Conduct Disorder: A Mega-Analysis of the ENIGMA Antisocial Behavior Working Group

Conduct disorder (CD) is the leading global cause of mental health burden in children and adolescents and has recently been hypothesized to be a neurodevelopmental disorder. Although prior research has identified neuroanatomical differences associated with CD, it remains unclear whether these differences reflect atypical brain development. Here, we investigated the difference between an individuals brain age and chronological age as a proxy for variations in brain maturation. Using a pretrained model, we estimated brain age from structural neuroimaging data obtained from 1,119 youth with CD and 1,183 typically developing controls across 14 international cohorts participating in the ENIGMA-Antisocial Behavior Working Group. Youth with CD exhibited a statistically robust but small acceleration in brain age compared to typically developing youth (around 0.50 years), which was restricted to the adolescence-onset subtype of the disorder. Our large-scale, coordinated analysis provides the first evidence of accelerated neurodevelopment as a potential mechanism underlying CD.

neuroscience↗

bioRxiv2025

Unifying DNA methylation-based in silico cell-type deconvolution with methyldeconv

SummaryCell-type deconvolution is widely applied to gene expression and DNA methylation data, but access to methods for the latter remains limited. We introduce deconvMe, a new R package that simplifies access to DNA methylation-based deconvolution methods predominantly for blood data, and we additionally compare their estimates to those from gene expression and experimental ground truth data using a unique matched blood dataset.

bioinformatics↗

bioRxiv2025

TRPV2 and TRPM2 channels facilitate pulmonary endothelial barrier recovery after ROS-induced permeability

Reactive oxygen species (ROS), such as hydrogen peroxide (H2O2), are known signaling molecules that increase endothelial barrier permeability. In this study, we investigated the roles of two redox-sensitive transient receptor potential (TRP) ion channels, TRPM2 and TRPV2, in H2O2- induced endothelial barrier dysfunction. Using primary human pulmonary microvascular endothelial cells (HPMEC), we employed impedance-based resistance measurements, Western blot, and immunofluorescence staining to assess the effects of H2O2 on the endothelial barrier. Exposure to sublytic concentrations of H2O2 caused an acute loss of endothelial barrier integrity, accompanied by the cleavage of vascular endothelial cadherin (VE-cadherin), which was also apparent after application of the TRPV2 activator cannabidiol. The inhibition of either TRPV2 with tranilast or a disintegrin and metalloprotease domain-containing protein 10 (ADAM10) with GI254023X significantly reduced H2O2-induced VE-cadherin cleavage, while TRPM2 inhibition by econazole significantly increased H2O2-driven VE-cadherin cleavage. Although inhibition of either TRP channel did not prevent the initial loss of barrier resistance upon H2O2 exposure, both were essential for the subsequent recovery of barrier integrity. Time-course immunofluorescence stainings revealed that HPMEC barrier recovery involved a transient localization of N-cadherin proteins at cell-cell junctions, which were replaced by VE-cadherin within 90 minutes. This process of cadherin-switching did not occur upon inhibition of TRPV2 or ADAM10. Our results highlight complementary roles for TRPM2 and TRPV2 as redox sensitive ion channels in the microvascular endothelium and provide insight into the mechanisms underlying pulmonary microvascular endothelial barrier recovery. Graphical Abstract: See text for more details O_FIG O_LINKSMALLFIG WIDTH=188 HEIGHT=200 SRC="FIGDIR/small/638083v1_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@5dbdacorg.highwire.dtl.DTLVardef@4f9bb5org.highwire.dtl.DTLVardef@77927dorg.highwire.dtl.DTLVardef@32894e_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

bioRxiv2024

TRPM7 activity drives human CD4 T-cell activation and differentiation in a magnesium dependent manner

T lymphocyte activation is a crucial process in the regulation of innate and adaptive immune responses. The ion channel-kinase TRPM7 has previously been implicated in cellular Mg2+ homeostasis, proliferation, and immune cell modulation. Here, we show that pharmacological and genetic silencing of TRPM7 leads to diminished human CD4 T-cell activation and proliferation following TCR mediated stimulation. In both primary human CD4 T cells and CRISPR/Cas-9 engineered Jurkat T cells, loss of TRPM7 led to altered Mg2+ homeostasis, Ca2+ signaling, reduced NFAT translocation, decreased IL-2 secretion and ultimately diminished proliferation and differentiation. While the activation of primary human CD4 T cells was dependent on TRPM7, polarization of naive CD4 T cells into regulatory T cells (Treg) was not. Taken together, these results highlight TRPM7 as a key protein of cellular Mg2+ homeostasis and CD4 T-cell activation. Its role in lymphocyte activation suggests therapeutic potential for TRPM7 in numerous T-cell mediated diseases. SummaryTRPM7 is crucial to maintaining cellular Mg2+ homeostasis and regulates human CD4 T-cell activation by modulating early Ca2+ signaling events in response to TCR-mediated stimulation subsequently, influencing T-cell differentiation in a Mg2+ dependent manner.

immunology↗

bioRxiv2024

R-Loop control and mitochondria genome stability requires the 5'-3' exonuclease/flap-endonuclease OEX1

Maintenance of the plant organelle genomes involves factors mostly inherited from their bacterial symbiotic ancestors. In bacteria, a major player in genome maintenance is DNA Polymerase I (Pol I), which provides a 5-3-exonuclease/flap-endonuclease activity required for multiple replication and repair functions. In plant organelles, DNA polymerases POL1A and POL1B are evolutionarily derived from DNA Pol I but lack this domain. In Arabidopsis, OEX1 and OEX2 (Organellar Exonucleases 1 and 2) represent this missing domain and are targeted to mitochondria and chloroplasts, respectively. An oex1 mutant allele shows developmental and fertility defects that correlate with the differential segregation of mitochondrial DNA (mtDNA) subgenomes generated by recombination, suggesting that OEX1 processes replication and recombination intermediates whose accumulation results in genome instability. Alternative splicing generates two OEX1 isoforms that can differentially interact with POL1A and POL1B and variably affect mtDNA repair. Recombinant OEX1 has 5-3-exonuclease and flap endonuclease activities, the latter being a key function in replication and repair. Furthermore, OEX1 has high affinity for RNA:DNA hybrids, rapidly degrading RNA in Okazaki-like structures and R-loops. Consistent with a role in suppressing R-loops, oex1 plants accumulate R-loops in highly transcribed mtDNA regions. Taken together, our results show that OEX1 plays multiple important roles in the processes required to maintain mtDNA stability.

plant biology↗

bioRxiv2024

Sex-specific role of epigenetic modification of a leptin upstream enhancer in the adipose tissue

ObjectiveMaternal hormonal status can have long-term effects on offspring metabolic health, likely regulated via epigenetic mechanisms. We elucidated the effect of maternal thyroid hormones on epigenetic regulation of Leptin (Lep) transcription in adipose tissue (AT) and investigated the role of DNA methylation at a Lep upstream enhancer (UE) in adipocyte biology. MethodsPregnant mice were treated with Triiodothyronine (T3). Offspring body composition and adipose tissue were analysed at 6 months (treatment: N = 8, control: N = 12). DNA methylation at the Lep UE and Lep mRNA levels in gonadal white adipose tissue (gWAT) and leptin serum levels were measured. The Lep UE was hypomethylated in murine preadipocytes using a dCas9-SunTag-TET1 system, followed by differentiation. In human visceral AT samples (N = 52) from the Leipzig Obesity BioBank (LOBB) LEP UE methylation and LEP mRNA levels were assessed alongside leptin serum levels and correlated with body fat percentage. Causal relationships were explored using mediation analysis. ResultsHigh maternal T3 levels reduced offspring body weight, total fat, and gWAT mass. Female offspring of T3-treated mothers showed lower Lep mRNA levels and higher Lep UE methylation compared to controls. CRISPR/dCas9 editing reduced Lep UE methylation by [~]20% in preadipocytes without altering Lep expression or lipid accumulation after differentiation. In humans, a mediation of sex-specific difference in body fat percentage via Lep UE methylation was found. ConclusionMaternal thyroid hormones might affect offspring gWAT Lep expression in a sex-specific manner, potentially driven by DNA methylation at the Lep UE, influencing body fat percentage.

genetics↗

bioRxiv2024

Benchmarking second-generation methods for cell-type deconvolution of transcriptomic data

BackgroundIn silico cell-type deconvolution from bulk transcriptomics data is a powerful technique to gain insights into the cellular composition of complex tissues. While first-generation methods used precomputed expression signatures covering limited cell types and tissues, second-generation tools use single-cell RNA sequencing data to build custom signatures for deconvoluting arbitrary cell types, tissues, and organisms. This flexibility poses significant challenges in assessing their deconvolution performance. ResultsHere, we comprehensively benchmark second-generation tools, disentangling different sources of variation and bias using a diverse panel of real and simulated data. Our results reveal substantial differences in accuracy, scalability, and robustness across methods, depending on factors such as cell-type similarity, reference composition, and dataset origin. Conclusions.Our study highlights the strengths, limitations, and complementarity of state-of-the-art tools, shedding light on how different data characteristics and confounders impact deconvolution performance. We provide the scientific community with an ecosystem of tools and resources, omnideconv, simplifying the application, benchmarking, and optimization of deconvolution methods.

bioinformatics↗

bioRxiv2023

Blood transcriptomics analysis offers insights into variant-specific immune response to SARS-CoV-2

Bulk RNA sequencing (RNA-seq) of blood is typically used for gene expression analysis in biomedical research but is still rarely used in clinical practice. In this study, we argue that RNA-seq should be considered a routine diagnostic tool, as it offers not only insights into aberrant gene expression and splicing but also delivers additional readouts on immune cell type composition as well as B-cell and T-cell receptor (BCR/TCR) repertoires. We demonstrate that RNA-seq offers vital insights into a patients immune status via integrative analysis of RNA-seq data from patients infected with various SARS-CoV-2 variants (in total 240 samples with up to 200 million reads sequencing depth). We compare the results of computational cell-type deconvolution methods (e.g., MCP-counter, xCell, EPIC, quanTIseq) to complete blood count data, the current gold standard in clinical practice. We observe varying levels of lymphocyte depletion and significant differences in neutrophil levels between SARS-CoV-2 variants. Additionally, we identify B and T cell receptor (BCR/TCR) sequences using the tools MiXCR and TRUST4 to show that - combined with sequence alignments and pBLAST - they could be used to classify a patients disease. Finally, we investigated the sequencing depth required for such analyses and concluded that 10 million reads per sample is sufficient. In conclusion, our study reveals that computational cell-type deconvolution and BCR/TCR methods using bulk RNA-seq analyses can supplement missing CBC data and offer insights into immune responses, disease severity, and pathogen-specific immunity, all achievable with a sequencing depth of 10 million reads per sample. Key PointsO_LIComputational deconvolution of transcriptomes can estimate immune cell abundances in SARS-CoV-2 patients, supplementing missing CBC data. C_LIO_LI10 million RNA sequencing reads per sample suffice for analyzing immune responses and disease severity, including BCR/TCR identification. C_LI

bioinformatics↗

bioRxiv2023

Diurnal rhythmicity of fecal microbiota and metabolite profiles in the first year of life: a randomized controlled interventional trial with infant formula

Microbiota assembly in the infant gut is influenced by time and duration of dietary exposure to breast-milk, infant formula and solid foods. In this randomized controlled intervention study, longitudinal sampling of infant stool (n=998) showed similar development of fecal bacterial communities (16S rRNA/shallow metagenomics sequencing) between formula- and breast-fed infants during the first year of life (N=210). Infant formula supplemented with galacto-oligosaccharides (GOS) was most efficient to sustain high levels of bifidobacteria compared to formula containing B. longum and B. breve or placebo. In addition to primary endpoints, metabolite and bacterial profiling revealed 24-hour oscillations and data integration identified circadian networks. Rhythmicity in bacterial diversity, specific taxa and functional pathways increased with age and was strongest following breast-feeding and GOS-supplementation. Circadian rhythms in dominant taxa were discovered ex-vivo in a chemostat model. Hence, microbiota rhythmicity develops early in life, likely via bacterial intrinsic clock mechanism and is affected by diet.

microbiology↗

bioRxiv2023

The landscape of tolerated genetic variation in humans and primates

Personalized genome sequencing has revealed millions of genetic differences between individuals, but our understanding of their clinical relevance remains largely incomplete. To systematically decipher the effects of human genetic variants, we obtained whole genome sequencing data for 809 individuals from 233 primate species, and identified 4.3 million common protein-altering variants with orthologs in human. We show that these variants can be inferred to have non-deleterious effects in human based on their presence at high allele frequencies in other primate populations. We use this resource to classify 6% of all possible human protein-altering variants as likely benign and impute the pathogenicity of the remaining 94% of variants with deep learning, achieving state-of-the-art accuracy for diagnosing pathogenic variants in patients with genetic diseases. One Sentence SummaryDeep learning classifier trained on 4.3 million common primate missense variants predicts variant pathogenicity in humans.

genomics↗

bioRxiv2023

Understanding the neural mechanisms of emotion-cognition interaction via high resolution mapping in space, time, frequency, and information transfer

Interactions between emotional and cognitive processing play a critical role in determining human behavior. The ability to efficiently control these interactions is essential for goal-directed behavior. Previous research on emotion-cognition interaction in humans has primarily focused on its neural topography using techniques with either low temporal resolution (fMRI) or low spatial resolution (ERP), leaving the underlying neuronal mechanisms and their behavioral implications poorly understood. Here, we used EEG recordings from a large cohort of human participants (N=121) and employed source-reconstruction with finite-element head modeling during an emotional Flanker task. Our findings reveal a neural interaction between emotional interference and cognitive control within the pars triangularis of the right inferior frontal gyrus (rIFG). These results align spatially and conceptually with meta-analytic evidence from fMRI studies on interference inhibition processes, supporting the idea that the rIFG is crucial for interference inhibition, regardless of the interfering information type. Notably, the neural interaction between emotion and cognition in the rIFG was transient, peaking during the transition from emotional to cognitive processing, and was most pronounced in the beta-frequency band. Furthermore, conditional Granger-causality analysis of information flow indicated that the pars triangularis of the rIFG communicated with other functional subdivisions of the rIFG and parieto-occipital areas (such as the Precuneus and V2) in a frequency-specific manner. This information flow predicted individual emotional and cognitive interference effects on behavior. Overall, our findings highlight the functional and temporal segregation and integration of emotion, cognition, and their interaction in the rIFG. Furthermore, rIFGs top-down modulation of visuo-attentional areas, ultimately shaping behavioral performance, underscores the importance of stimulus interference inhibition for emotion-cognition interaction. Author summaryUnderstanding the interplay between emotion and cognition is crucial for understanding human behavior. Our study investigates the role of transient oscillatory activity using source-localized EEG in a large cohort. We identify a spatial overlap of the interaction of emotion and cognition processing in the rIFGs pars triangularis, aligning closely with localizations indicated by meta-analytic fMRI evidence. This interaction, primarily in the beta-frequency (around 20Hz) band, is transient, peaking during the shift from emotional to cognitive processing. Granger-causality analysis reveals frequency-specific communication patterns within the rIFG and parieto-occipital areas, predicting individual emotional and cognitive interference effects. Our findings elucidate the functional and temporal dynamics of emotion-cognition interaction within the rIFG, providing insights into the nuanced neural processes shaping human behavior.

neuroscience↗

bioRxiv2022

SimBu: Bias-aware simulation of bulk RNA-seq data with variable cell type composition

MotivationAs complex tissues are typically composed of various cell types, deconvolution tools have been developed to computationally infer their cellular composition from bulk RNA sequencing (RNA-seq) data. To comprehensively assess deconvolution performance, gold-standard datasets are indispensable. Gold-standard, experimental techniques like flow cytometry or immunohistochemistry are resource-intensive and cannot be systematically applied to the numerous cell types and tissues profiled with high-throughput transcriptomics. The simulation of pseudo-bulk data, generated by aggregating single-cell RNA-seq (scRNA-seq) expression profiles in pre-defined proportions, offers a scalable and cost-effective alternative. This makes it feasible to create in silico gold standards that allow fine-grained control of cell-type fractions not conceivable in an experimental setup. However, at present, no simulation software for generating pseudo-bulk RNA-seq data exists. ResultsWe developed SimBu, an R package capable of simulating pseudo-bulk samples based on various simulation scenarios, designed to test specific features of deconvolution methods. A unique feature of SimBu is the modelling of cell-type-specific mRNA bias using experimentally-derived or data-driven scaling factors. Here, we show that SimBu can generate realistic pseudo-bulk data, recapitulating the biological and statistical features of real RNA-seq data. Finally, we illustrate the impact of mRNA bias on the evaluation of deconvolution tools and provide recommendations for the selection of suitable methods for estimating mRNA content. ConclusionSimBu is a user-friendly and flexible tool for simulating realistic pseudo-bulk RNA-seq datasets serving as in silico gold-standard for assessing cell-type deconvolution methods. AvailabilitySimBu is freely available at https://github.com/omnideconv/SimBu as an R package under the GPL-3 license. Contactalex.dietrich@tum.de and markus.list@tum.de Supplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗

bioRxiv2022

An Inhibitory Function of TRPA1 Channels in TGF-β1-driven Fibroblast to Myofibroblast Differentiation

Transient receptor potential ankyrin 1 (TRPA1) is a non-selective Ca2+ permeable cation channel, which was originally cloned from human lung fibroblasts (HLFs). TRPA1-mediated Ca2+ entry is evoked by exposure to several chemicals, including allyl isothiocyanate (AITC), and a protective effect of TRPA1 activation in the development of cardiac fibrosis has been proposed. Yet, the function of TRPA1 in transforming growth factor {beta}1 (TGF-{beta}1)-driven fibroblast to myofibroblast differentiation and the development of pulmonary fibrosis remains elusive. TRPA1 expression and function was analyzed in cultured primary HLFs, and mRNA levels were significantly reduced after adding TGF-{beta}1. Expression of genes encoding fibrosis markers, e.g. alpha smooth muscle actin (ACTA2), plasminogen activator inhibitor 1 (SERPINE1), fibronectin (FN1) and type I collagen (COL1A1) was increased after siRNA-mediated down-regulation of TRPA1-mRNA in HLFs. Moreover, AITC-induced Ca2+ entry in HLFs was decreased after TGF-{beta}1 treatment and by application of TRPA1 siRNAs, while AITC treatment alone did not reduce cell viability or enhanced apoptosis. Cell barrier function increased after addition of TRPA1 siRNAs or TGF-{beta}1 treatment. Most interestingly, AITC-induced TRPA1 activation augmented ERK1/2 phosphorylation, which might inhibit TGF-{beta}-receptor signaling. Our results suggest an inhibitory function of TRPA1 channels in TGF-{beta}1-driven fibroblast to myofibroblast differentiation. Therefore, activation of TRPA1 channels might be protective during the development of pulmonary fibrosis in patients.

cell biology↗

bioRxiv2022

Alternative splicing analysis benchmark with DICAST

Alternative splicing is a major contributor to transcriptome and proteome diversity in health and disease. A plethora of tools have been developed for studying alternative splicing in RNA-seq data. Previous benchmarks focused on isoform quantification and mapping. They neglected event detection tools, which arguably provide the most detailed insights into the alternative splicing process. DICAST offers a modular and extensible framework for the analysis of alternative splicing integrating 11 splice-aware mapping and eight event detection tools. We benchmark all tools extensively on simulated as well as whole blood RNA-seq data. STAR and HISAT2 demonstrated the best balance between performance and run time. The performance of event detection tools varies widely with no tool outperforming all others. DICAST allows researchers to employ a consensus approach to consider the most successful tools jointly for robust event detection. Furthermore, we propose the first reporting standard to unify existing formats and to guide future tool development.

bioinformatics↗

bioRxiv2021

Namco: A microbiome explorer

16S rRNA gene profiling is currently the most widely used technique in microbiome research and allows for studying microbial diversity, taxonomic profiling, phylogenetics, functional and network analysis. While a plethora of tools have been developed for the analysis of 16S rRNA gene data, only a few platforms offer a user-friendly interface and none comprehensively covers the whole analysis pipeline from raw data processing down to complex analysis. We introduce Namco, an R shiny application that offers a streamlined interface and serves as a one-stop solution for microbiome analysis. We demonstrate Namcos capabilities by studying the association between a rich fibre diet and the gut microbiota composition. Namco helped to prove the hypothesis that butyrate-producing bacteria are prompted by fibre-enriched intervention. Namco provides a broad range of features from raw data processing and basic statistics down to machine learning and network analysis, thus covering complex data analysis tasks that are not comprehensively covered elsewhere. Namco is freely available at https://exbio.wzw.tum.de/Namco/. Impact statementAmplicon sequencing is a key technology of microbiome research and has yielded many insights into the complexity and diversity of microbiota. To fully leverage these data, a wide range of tools have been developed for raw data processing, normalization, statistical analysis and visualization. These tools are mostly available as R packages but cannot be easily linked in an automated pipeline due to the heterogeneous characteristics of microbiome data. Instead, user-friendly tools for explorative analysis are needed to give biomedical researchers without experience in scripting languages the possibility to fully exploit their data. Several tools for microbiome data analysis have been proposed in recent years which cover a broad range of functionality but few offer a user-friendly and beginner-friendly interface while covering the entire value whole value chain from raw data processing down to complex analysis. With Namco(https://exbio.wzw.tum.de/namco/), we present a beginner-friendly one-stop solution for microbiome analysis that covers upstream analyses like raw data processing, taxonomic binning and downstream analyses like basic statistics, machine learning and network analysis, among other features.

bioinformatics↗