Biology subjects

Mardinoglu, A.

Publications and source records attributed to Mardinoglu, A..

At least 19 recordsLinked to original sources

bioRxiv2026

Metacontam: A Negative Control-Free Decontamination Method for Metagenomic Analysis

Shotgun metagenomic sequencing enables high-resolution profiling of host-associated microbial communities. However, contaminant DNA can substantially distort biological interpretations, especially in low-biomass samples. Here, we introduce Metacontam, a control-free method for species-level decontamination of shotgun metagenomic data. Metacontam integrates blacklist-guided community detection within a species correlation network with average nucleotide identity (ANI) to identify contaminants arising from shared sources. Across diverse low-biomass and mixed-biomass datasets, Metacontam outperformed existing approaches, improving the detection of low-abundance and low-prevalence contaminants while retaining biologically plausible taxa. It also reduces kit-specific biases in skin metagenomes and improves downstream analyses of tissue microbiome data. Together, these results demonstrate that Metacontam enables accurate identification of contaminant taxa across diverse metagenomic datasets, even in the absence of negative controls.

bioinformatics↗

bioRxiv2026

G-VEP: GPU-Accelerated Variant Effect Prediction for Clinical Whole-Genome Sequencing Analysis

Whole-genome sequencing (WGS) has transformed clinical diagnostics, yet variant annotation remains a computational bottleneck. The Variant Effect Predictor (VEP) integrates pathogenicity predictors and population databases essential for ACMG/AMP variant classification, but these annotation plugins are fundamentally I/O-bound, consuming over 70% of total pipeline runtime. Here, we present G-VEP, a GPU-accelerated annotation framework built on a custom CUDA kernel that replaces sequential per-variant database lookups with massively parallel binary search across precomputed indices. By executing annotation lookups for all input variants simultaneously, G-VEP reduces plugin runtime from 72 minutes to 4 minutes (17-fold acceleration) and total annotation runtime from 100 minutes to 33 minutes (3-fold acceleration), while maintaining complete concordance with standard VEP output. Benchmarking across 75 clinical WGS samples demonstrated consistent performance, with no annotation discrepancies; validation on samples containing known pathogenic variants confirmed the preservation of all clinically significant findings. The 8.8 GB index footprint fits within consumer-grade 16 GB GPUs. G-VEP addresses an unmet need in clinical WGS analysis, while GPU suites such as NVIDIA Parabricks accelerate alignment and variant calling, they do not provide the Ensembl VEP plugin ecosystem used in clinical interpretation. G-VEP removes this final bottleneck and enables accelerated WGS interpretation. G-VEP is freely available through a web-based user interface with REST API documentation at https://www.phenomeportal.org/gvep, and source code for local installation and deployment at https://github.com/Phenome-Longevity/G-VEP.

bioinformatics↗

bioRxiv2026

Systematic Analysis of Human Tissue- and Cell-Specific Metabolic Models Identifies High-Sugar, High Fat Diet Induced Liver Dysregulation

Human tissues exhibit specialized metabolic functions that are essential for maintaining whole-body metabolic homeostasis. To systematically characterize organ- and cell-type-specific metabolic heterogeneity, we constructed 32 tissue-specific and 81 cell-type-specific enzyme-constrained genome-scale metabolic models (ecGEMs) by integrating the global human metabolic network with the tissue- and single-cell transcriptomic data from the Human Protein Atlas (HPA). Our analysis revealed pronounced differences in metabolic network architecture and activity across the human body, identifying key cell types that drive tissue metabolic functions. To demonstrate the applicability of these models, we employed the liver-specific ecGEM to investigate the metabolic reprogramming induced by a high-sugar, high-fat (HSHF) diet, a primary driver of metabolic dysfunction-associated fatty liver disease (MAFLD). Flux balance analysis revealed a fundamental transition in hepatic metabolism: from a flexible, multi-functional system toward a constrained, lipid-centric regime. This state is characterized by carbohydrate and lipid overload, mitochondrial respiratory dysfunction, and a compromised capacity for reactive oxygen species (ROS) detoxification. These computational predictions were validated through integrative analysis of transcriptomic data from a human MAFLD cohort and metabolomic profiles from an in vivo HSHF rat model. Together, this work provides a comprehensive atlas of human metabolic models, enabling the systematic investigation of metabolic features across tissues and conditions from a systems-level perspective. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=142 SRC="FIGDIR/small/706568v1_ufig1.gif" ALT="Figure 1"> View larger version (40K): org.highwire.dtl.DTLVardef@1015c7org.highwire.dtl.DTLVardef@5c200org.highwire.dtl.DTLVardef@3c982org.highwire.dtl.DTLVardef@a2894d_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2025

Microbial oral-gut translocation in advanced chronic liver disease is linked to exacerbation of intestinal barrier dysfunction and hepatic fibrosis

While microbiome perturbations are associated with advanced chronic liver disease (ACLD), microbial disease mechanisms are poorly understood. Using multi-omics analyses of paired saliva and faecal samples from an ACLD cohort, we identified next-to-identical oral and gut bacterial strains (including Veillonella and Streptococcus spp.) which increased in absolute abundance in the gut of ACLD patients. These translocators uniquely encoded a collagenase-like proteinase (prtC) with the potential for gut barrier disruption and prtC faecal abundance was a robust ACLD biomarker (auPR=0.91). CCl4-treated mice inoculated with Veillonella and Streptococcus prtC-encoding patient isolates showed exacerbation of gut barrier impairment and hepatic fibrosis. Furthermore, faecal collagenase activity was increased in ACLD patients and experimentally confirmed for the prtC gene from translocating Veillonella parvula. Overall, our study establishes mechanistic links between oral-gut translocation and ACLD pathobiology, and identifies the oral microbiome as an important contributing factor with potential for microbial diagnostics and therapeutics.

microbiology↗

bioRxiv2025

Integrative Analysis of Left Ventricle and Epicardial Adipose Tissue Identifies SDHA and OGDH as Candidate Targets for Ischemic Heart Disease

Ischemic heart disease (IHD) involves coordinated molecular changes across heart, yet their interplay remains poorly understood. Here, we investigated transcriptomic alterations in two heart tissue subtypes, left ventricle (LV) and epicardial adipose tissue (EAT), from age- and BMI-matched healthy and IHD individuals, including both diabetic and non-diabetic patients. We performed transcriptomic profiling and systems-level network analysis to identify disease-associated gene expression changes. Our analysis revealed: (1) stronger transcriptional responses in EAT compared to LV, particularly in diabetic individuals, and (2) widespread dysregulation of inflammatory and metabolic pathways, including oxidative phosphorylation, cytokine signaling, and fatty acid degradation, across both tissue subtypes. Co-expression network analysis uncovered shared gene modules, with SDHA (Succinate dehydrogenase complex, subunit A) and OGDH (Oxoglutarate Dehydrogenase) emerging as central, downregulated genes linked to mitochondrial function and inflammation, important processes in IHD pathophysiology. These findings were validated in independent human and mouse datasets. Overall, our integrative analysis identifies conserved molecular signatures across cardiac tissue subtypes, suggesting potential for therapeutic exploration in IHD. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=140 SRC="FIGDIR/small/676232v1_ufig1.gif" ALT="Figure 1"> View larger version (38K): org.highwire.dtl.DTLVardef@7e17eeorg.highwire.dtl.DTLVardef@552321org.highwire.dtl.DTLVardef@1755f30org.highwire.dtl.DTLVardef@bc5872_HPS_FORMAT_FIGEXP M_FIG C_FIG

systems biology↗

bioRxiv2024

Microbiome signatures of virulence in the oral-gut-brain axis influence Parkinson's disease and cognitive decline pathophysiology

The human microbiome is increasingly recognized for its crucial role in the development and progression of neurodegenerative diseases. While the gut-brain axis has been extensively studied, the contribution of the oral microbiome and gut-oral tropism in neurodegeneration has been largely overlooked. Cognitive impairment (CI) is common in neurodegenerative diseases and develops on a spectrum. In Parkinsons Disease (PD) patients, CI is one of the most common non-motor symptoms but its mechanistic development across the spectrum remains unclear, complicating early diagnosis of at-risk individuals. Here, we generated 228 shotgun metagenomics samples of the gut and oral microbiomes across PD patients with either mild cognitive impairment (PD-MCI) or dementia (PDD), and a healthy cohort, to study the role of the gut and oral microbiomes on CI in PD. In addition to revealing compositional and functional signatures, the role of pathobionts, and dysregulated metabolic pathways of the oral and gut microbiome in PD-MCI and PDD, we also revealed the importance of oral-gut translocation in increasing abundance of virulence factors in PD and CI. The oral-gut virulence was further integrated with saliva metaproteomics and demonstrated their potential role in dysfunction of host immunity and brain endothelial cells. Our findings highlight the significance of the oral-gut-brain axis and underscore its potential for discovering novel biomarkers for PD and CI.

microbiology↗

bioRxiv2024

Extensively acquired antimicrobial resistant bacteria restructure the individual microbial community in post-antibiotic conditions

In recent years, the overuse of antibiotics has led to the emergence of antimicrobial resistant (AMR) bacteria. To evaluate the spread of AMR bacteria, the reservoir of AMR genes (resistome) has traditionally been identified from environmental samples, hospital environments, and human populations; however, the functional role of AMR bacteria in the human gut microbiome and their persistency within individuals has not been fully investigated. Here, we performed a strain-resolved in-depth analysis of the resistome changes by reconstructing a large number of metagenome-assembled genomes (MAGs) of antibiotics- treated individuals gut microbiome. Interestingly, we identified two bacterial populations with different resistome profiles, extensively acquired antimicrobial resistant bacteria (EARB) and sporadically acquired antimicrobial resistant bacteria (SARB), and found that EARB showed broader drug resistance and a significant functional role in shaping individual microbiome composition after antibiotic treatment. Furthermore, longitudinal strain analysis revealed that EARB bacteria were inherently carried by individuals and can reemerge through strain switching in the human gut microbiome. Our data on the presence of AMR bacteria in the human gut microbiome provides a new avenue for controlling the spread of AMR bacteria in the human community.

genomics↗

bioRxiv2024

Multi-tissue network analysis reveals the effect of JNK inhibition on dietary sucrose-induced metabolic dysfunction in rats

Excessive consumption of sucrose, in the form of sugar-sweetened beverages, has been implicated in the pathogenesis of metabolic dysfunctionLassociated fatty liver disease (MAFLD) and other related metabolic syndromes. The c-Jun N-terminal kinase (JNK) pathway plays a crucial role in response to dietary stressors, and it was demonstrated that the inhibition of the JNK pathway could potentially be used in the treatment of MAFLD. However, the intricate mechanisms underlying these interventions remain incompletely understood given their multifaceted effects across multiple tissues. In this study, we challenged rats with sucrose-sweetened water and investigated the potential effects of JNK inhibition by employing network analysis based on the transcriptome profiling obtained from hepatic and extrahepatic tissues, including visceral white adipose tissue, skeletal muscle, and brain. Our data demonstrate that JNK inhibition by JNK-IN-5A effectively reduces the circulating triglyceride accumulation and inflammation in rats subjected to sucrose consumption. Coexpression analysis and genome-scale metabolic modelling reveal that sucrose overconsumption primarily induces transcriptional dysfunction related to fatty acid and oxidative metabolism in the liver and adipose tissues, which are largely rectified after JNK inhibition at a clinically relevant dose. Skeletal muscle exhibited minimal transcriptional changes to sucrose overconsumption but underwent substantial metabolic adaptation following the JNK inhibition. Overall, our data provides novel insights into the molecular basis by which JNK inhibition exerts its metabolic effect in the metabolically active tissues. Furthermore, our findings underpin the critical role of extrahepatic metabolism in the development of diet-induced steatosis, offering valuable guidance for future studies focused on JNK-targeting for effective treatment of MAFLD.

bioinformatics↗

bioRxiv2023

Multi-omics characterization of lymphedema-induced adipose tissue from breast cancer patients

ObjectiveSecondary lymphedema (LE) following breast cancer surgery is a life-long complication, which currently has no cure. LE induces significant regional adipose tissue deposition, requiring liposuction as a treatment. Here, we aimed to elucidate the transcriptional, metabolomic, and lipidomic signature of the adipose tissue developed due to the surgery-induced LE in short- and long-term LE patients, and compared the transcriptomic landscape in LE to the obesity-induced adipose tissue. MethodsAdipose tissue biopsies were obtained from breast cancer-operated females with LE from the affected and non-affected arms (n=20 patients). To decipher molecular properties of the LE adipose tissue, we performed RNA sequencing, metabolomics, and lipidomics combined with bioinformatics analyses. ResultsIntegrative analysis of functional genomics revealed that inflammatory response, cell chemotaxis and angiogenesis were upregulated biological processes in the LE arm, indicating a sustained inflammation in the edematous adipose tissue, whereas, epidermal differentiation, cell-cell junction organization, water homeostasis and neurogenesis were, in turn, downregulated in the LE arm. Surprisingly, only few genes were found to be the same in the LE-induced and the obesity-induced adipose tissue expansion, indicating a different type of adipose tissue development in these two diseases. In metabolomics analysis, the concentration of a branched-chain amino acid valine was found to be reduced in the edematous arm together with downregulation of mRNA levels of its transporter SLC6A15. Lipidomics analyses did not show any significant differences between the diseased and healthy arm, suggesting that diet affects the lipid composition of the adipose tissue more than the LE. ConclusionsOur results provide a detailed molecular characterization of adipose tissue in secondary LE of breast cancer patients vs individuals with obesity. The results show distinct differences in transcriptomic signatures between LE patients vs individuals with obesity, but only minor differences in metabolome and lipidome between the diseased and the healthy arm.

pathology↗

bioRxiv2023

Pathogenic entero- and salivatypes harbour changes in microbiome virulence and antimicrobial resistance genes with increasing chronic liver disease severity

Background & AimsLife-threatening complications of cirrhosis are triggered by bacterial infections, with the ever-increasing threat of antimicrobial resistance (AMR). Alterations in the gut microbiome in decompensated cirrhosis (DC) and acute-on-chronic liver failure (ACLF) are recognised to influence clinical outcomes, whilst the role of the oral microbiome is still being explored. Our aims were to simultaneously interrogate the gut and oral micro- and mycobiome in cirrhotic patients, and assess microbial community structure overlap in relation to clinical outcomes, as well as alterations in virulence factors and AMR genes. Methods18 healthy controls (HC), 20 stable cirrhotics (SC), 50 DC, 18 ACLF and 15 with non-liver sepsis (NLS) i.e. severe infection but without cirrhosis, were recruited at a tertiary liver centre. Shotgun metagenomic sequencing was undertaken from saliva (S) and faecal (F) samples (paired where possible). Salivatypes and enterotypes based on clustering of genera were calculated and compared in relation to cirrhosis severity and in relation to specific clinical parameters. Virulence and antimicrobial resistance genes (ARGs) were evaluated in both oral and gut niches, and distinct resistotypes identified. ResultsSpecific saliva- and enterotypes revealed a greater proportion of pathobionts with concomitant reduction in autochthonous genera with increasing cirrhosis severity, and in those with hyperammonemia. Overlap between oral and gut microbiome communities was observed and was significantly higher in DC and ACLF vs SC and HCs, independent of antimicrobial, beta-blocker and acid suppressant use. Two distinct gut microbiome clusters [ENT2/ENT3] harboured genes encoding for the phosphoenolpyruvate:sugar phosphotransferase system (PTS) system and other virulence factors in patients with DC and ACLF. Substantial numbers of ARGs (oral: 1,218 and gut: 672) were detected with 575 ARGs common to both sites. The cirrhosis resistome was significantly different to HCs, with three and four resistotypes identified for the oral and gut microbiome, respectively. DiscussionOral and gut microbiome profiles differ significantly with increasing severity of cirrhosis, with progressive dominance of pathobionts and loss of commensals. DC and ACLF have significantly worse microbial diversity than NLS, despite similar antimicrobial exposure, supporting the additive patho-biological effect of cirrhosis. The degree of microbial community overlap between sites, frequency of virulence factors and presence of ARGs, all increment significantly with hepatic decompensation. These alterations may predispose to higher infection risk, poorer response to antimicrobial therapy and worsening outcomes, and provide the rationale for developing non-antibiotic-dependent microbiome-modulating therapies.

physiology↗

bioRxiv2023

Molecular profiling of high-level athlete skeletal muscle after acute exercise - a systems biology approach

Life-long high-level exercise training leads to improvements in physical performance and multi-tissue adaptation following changes in molecular pathways. While skeletal muscle baseline differences between exercise-trained and untrained individuals have been previously investigated, it remains unclear how acute exercise multi-omics are influenced by training history. We recruited and extensively characterized 24 individuals categorized as endurance athletes, strength athletes or control subjects. Multi-omics profiling was performed from skeletal muscle before and at three time-points after endurance or resistance exercise sessions. Timeseries multi-omics analysis revealed distinct differences in molecular processes such as fatty- and amino acid metabolism and for transcription factors such as HIF1A and the MYF-family between both exercise history and acute form of exercise. Furthermore, we found a "transcriptional specialization effect" by transcriptional narrowing and intensification. Finally, we performed multi-omics network analysis and clustering, providing a novel resource of skeletal muscle transcriptomic and metabolomic profiling in highly trained and untrained individuals.

physiology↗

bioRxiv2023

standard-GEM: standardization of open-source genome-scale metabolic models

The field of metabolic modelling at the genomescale continues to grow with more models being created and curated. This comes with an increasing demand for adopting common principles regarding transparency and versioning, in addition to standardisation efforts regarding file formats, annotation and testing. Here, we present a standardised template for git-based and GitHub-hosted genome-scale metabolic models (GEMs) supporting both new models and curated ones, following FAIR principles (findability, accessibility, interoperability, and reusability), and incorporating bestpractices. standard-GEM facilitates the reuse of GEMs across web services and platforms in the metabolic modelling field and enables automatic validation of GEMs. The use of this template for new models, and its adoption for existing ones, paves the way for increasing model quality, openness, and accessibility with minimal effort. Availabilitystandard-GEM is available from github.com/MetabolicAtlas/standard-GEM under the conditions of the CC BY 4.0 licence along with additional supporting material.

systems biology↗

bioRxiv2022

Genome-wide single cell annotation of the human protein-coding genes

An important quest for the life science community is to deliver a complete annotation of the human building-blocks of life, the genes and the proteins. Here, we report on a genome-wide effort to annotate all protein-coding genes based on single cell transcriptomics data representing all major tissues and organs in the human body, integrated with data from bulk transcriptomics and antibody-based tissue profiling. Altogether, 25 tissues have been analyzed with single cell transcriptomics resulting in genome-wide expression in 444 single cell types using a strategy involving pooling data from individual cells to obtain genome-wide expression profiles of individual cell type. We introduce a new genome-wide classification tool based on clustering of similar expression profiles across single cell types, which can be visualized using dimensional reduction maps (UMAP). The clustering classification is integrated with a new "tau" score classification for all protein-coding genes, resulting in a measure of single cell specificity across all cell types for all individual genes. The analysis has allowed us to annotate all human protein-coding genes with regards to function and spatial distribution across individual cell types across all major tissues and organs in the human body. A new version of the open access Human Protein Atlas (www.proteinatlas.org) has been launched to enable researchers to explore the new genome-wide annotation on an individual gene level.

systems biology↗

bioRxiv2022

Hexokinase 1b is a novel target for non-small-cell lung cancer

Deregulation of glycolysis is common in non-small cell lung cancer (NSCLC). Hexokinase (HK) enzymes catalyze the phosphoryl-group-transfer in glucose metabolism. There are a very few studies that have begun to reveal the connections between glucose metabolism and splicing programs. Unlike HK2 gene, which is expressed as a single transcript, there are several transcripts of the HK1 gene due to alternative splicing. However, the functional differential roles of HK1 isoforms in glucose metabolism and tumor progression are still elusive. Here, we show that primary NSCLC patient tumor cells metabolically differ from the normal lung epithelium where they display predominant expression of one of the HK1 transcripts, hexokinase1b (HK1b). We utilized CRISPR-Cas9 system to selectively target specific HK1b isoform in NSCLC and show that silencing HK1b in NSCLC cells inhibits tumorigenesis through diminishing glycolysis and proliferation. Our findings constitute the first demonstration of the first biochemical distinction between the HK1 splice variants. Finally, HK1b deletion sensitizes NSCLC cells to standard-of-care, cisplatin treatment, and the combination therapy synergistically increases both apoptotic cell death by cisplatin and autophagic cell death by increased formation of LC3-II associated autophagic vesicles and myelinoid bodies. Notably, loss of HK1b leads to cellular DNA damage, further combination with cisplatin therapy showed significantly increased levels of DNA damage. Importantly, we showed that glycolysis and cisplatin resistance can be restored by adding-back HK1b in HK1b knock-out cells. Our findings reveal that targeting HK1b isoform alone or in combination with cisplatin may represent a novel strategy for NSCLC patients.

cancer biology↗

bioRxiv2022

Network-based multi-omics integration reveals metabolic risk profile within treated HIV-infection

Multiomics technologies improve the biological understanding of health status in people living with HIV on antiretroviral therapy (PLWHART). Still, a systematic and in-depth characterization of metabolic risk profile during successful long-term treatment is lacking. Here, we used multi-omics (plasma lipidomic and metabolomic, and fecal 16s microbiome) data-driven stratification and characterization to identify the metabolic at-risk profile within PLWHART. Through network analysis and similarity network fusion (SNF), we identified three groups of PLWHART (SNF-1 to 3). The PLWHART at SNF-2 (45%) was a severe at-risk metabolic profile with increased visceral adipose tissue, BMI, higher incidence of metabolic syndrome (MetS), and increased di- and triglycerides despite having higher CD4+ T-cell counts than the other two clusters. However, the healthy-like and severe at-risk group had a similar metabolic profile differing from HC, with dysregulation of amino acid metabolism. At the microbiome profile, the healthy-like group had a lower -diversity, a lower proportion of MSM, and was enriched in Bacteroides. In contrast, in at-risk groups, there was an increase in Prevotella, with a high proportion of men who have sex with men (MSM) confirming the influence of sexual orientation on the microbiome profile The multi-omics integrative analysis reveals a complex microbial interplay by microbiome-derived metabolites in PLWHART. PLWHART those are severely at-risk clusters may benefit from personalized medicine and lifestyle intervention to improve their metabolic profile. SignificanceThe network and factorization-based integrative analysis of plasma metabolomics, lipidomics, and microbiome profile identified three different diseases state -omics phenotypes within PLWHART driven by metabolomics, lipidomics, and microbiome that a single omics or clinical feature could not explain. The severe at-risk group has a dysregulated metabolic profile that potentiates metabolic diseases that could be barriers to healthy aging. The at-risk group may benefit from personalized medicine and lifestyle intervention to improve their metabolic profile.

bioinformatics↗

bioRxiv2022

Discovery of therapeutic agents targeting PKLR for NAFLD using drug repositioning

Background & AimsNon-alcoholic fatty liver disease (NAFLD) encompasses a wide spectrum of liver pathologies. However, not medical treatment has been approved for the treatment of the disease. In our previous study, we found PKLR could be a potential target for treatment of NALFD. Here, the aim is to investigate the effect of PKLR in in vivo model and perform drug repositioning to identify a drug candidate for treatment of NAFLD. MethodsBiopsies from liver, muscle, white adipose tissue and heart were obtained from control and PKLR knockout mice fed with chow and high sucrose diets. Lipidomics as well as transcriptmics analyses were conducted using these tissue samples. In addition, a computational drug repositioning analysis was performed and drug candidates were identified. The drug candidates were finally tested in both in vitro and in vivo models to evaluated their toxicity and efficacy. ResultsThe Pklr KO reversed the increased hepatic triglyceride level in mice fed with high sucrose diet and partly recovered the transcriptomic changes in liver as well as other three tissues. Both liver and white adipose tissues exhibited dysregulated circadian transcriptomic profiles, and these dysregulations were reversed by hepatic knockout of Pklr. In addition, 10 small molecule drugs were identified as potential inhibitor of PKLR by the drug repositioning pipeline, and two of them significantly inhibited both the PKLR expression and triglyceride level in in vitro model. Finally, the two selected small molecule drugs were evaluated in in vivo rat models and it was demonstrated that these drugs attenuated hepatic steatosis without side effect on other tissues. ConclusionIn conclusion, our study provided biological insights about the critical role of PKLR in NAFLD progression and proposed a treatment strategy for NAFLD patients, which has been validated in preclinical experiment.

systems biology↗

bioRxiv2021

GutMicroNet: an interactive platform for gut microbiome interaction exploration

The human gut microbiome data has been proven to be a powerful tool to understand the human body in both health and disease conditions. However, understanding their complex interactions and impact on the human body remains a challenging task. Unravelling the species-level interactions could allow us to study the causality of the microbiome. Moreover, it could lead us to better understand the underlying mechanisms of complex diseases and, subsequently, the discovery of new therapeutic targets. Given these challenges and benefits, it has become evident that a freely accessible and centralized platform for presenting gut microbiome interaction is essential to untangle the complexity and open multiple new paths and opportunities in disease- and drug-related research. Here, we present GutMicroNet, an interactive visualization platform of human gut microbiome interaction networks. We generated 45 gut microbiome co-abundance networks from various geographical origins, gender, and diseases based on the data presented in the Human Gut Microbiome Atlas. This interactive platform includes more than 1900 gut microbiome species and allows users to query multiple species at the same time based on their interests and adjust it based on the statistical properties. Moreover, users can download publication-ready figures or network information for further analysis. The platform can be accessed freely on https://gutmicro.net without any login requirements or limitations, including access to the full networks data.

systems biology↗

bioRxiv2021

Stratification of the Gut Microbiota Composition Landscape Across the Alzheimer's Disease Continuum in a Turkish Cohort

Alzheimers disease (AD) is a heterogeneous neurodegenerative disorder that spans over a continuum with multiple phases including preclinical, mild cognitive impairment, and dementia. Unlike most other chronic diseases there are limited number of human studies reporting on AD gut microbiota in the literature. These published studies suggest that the gut microbiota of AD continuum patients varies considerably throughout the disease stages, raising expectations for existence of multiple microbiota community types. However, the community types of AD gut microbiota were not systematically investigated before, leaving important research gap for diet-based intervention studies and recently initiated precision nutrition approaches aiming at stratifying patients into distinct dietary subgroups. Here, we comprehensively assessed the community types of gut microbiota across the AD continuum. We analyze 16S rRNA amplicon sequencing of stool samples from 27 mild cognitive patients, 47 AD, and 51 non-demented control subjects using tools compatible with compositional nature of microbiota. To characterize gut microbiota community types, we applied multiple machine learning techniques including partitioning around the medoid clustering, fitting probabilistic Dirichlet mixture model, Latent Dirichlet Allocation model, and performed topological data analysis for population scale microbiome stratification based on Mapper algorithm. These four distinct techniques all converge on Prevotella and Bacteroides partitioning of the gut microbiota across AD continuum while some methods provided fine scale resolution in partitioning the community landscape. The Signature taxa and neuropsychometric parameters together robustly classify the heterogenous groups within the cohort. Our results provide a framework for precision nutrition approaches and diet-based intervention studies targeting AD cohorts. IMPORTANCEThe prevalence of AD worldwide is estimated to reach 131 million by 2050. Most disease modifying treatments and drug trials have failed due partly to the heterogeneous and complex nature of the disease. Unlike other neurodegenerative diseases gut microbiota of AD patients is poorly studied. Recently initiated ambitious precision nutrition initiative or other diet-based interventions can potentially be more effective if the heterogeneous disease such as AD is deconstructed into multiple strata allowing for better identification of biomarkers across narrower patient population for improved results. Because gut microbiota is inherently integral part of the nutritional interventions there is unmet need for microbiota-informed stratification of AD clinical cohorts in nutritional studies. Our study fills in this gap and draws attention to the need for microbiota stratification as one of the essential steps for precision nutrition interventions. We demonstrate that while Prevotella and Bacteroides clusters are the consensus partitions the newly developed probabilistic methods can provide fine scale resolution in partitioning the AD gut microbiome landscape.

microbiology↗