Biology subjects

Li, R.

Publications and source records attributed to Li, R..

At least 199 records · Page 11Linked to original sources

bioRxiv2025

mcDETECT: Decoding 3D Spatial Synaptic Transcriptomes with Subcellular-Resolution Spatial Transcriptomics

Spatial transcriptomics (ST) is a powerful tool for studying the molecular basis of brain diseases. However, most current analyses focus only on nuclear or somatic expression, overlooking distally localized mRNAs, known as the "dark transcriptome." These transcripts, which make up nearly 40% of the brain transcriptome, are packaged into RNA granules and transported to polarized neuronal structures critical for neuronal function. Here, we present mcDETECT, a machine learning framework that leverages in situ ST (iST) data to detect RNA granules and resolve their RNA composition. Applying mcDETECT to simulated and real datasets from multiple iST platforms, we demonstrate robust granule detection and molecular subtyping. Granule-informed downstream analysis further revealed functionally distinct neuronal substates not captured by somatic expression alone. In an Alzheimers disease (AD) mouse model, mcDETECT uncovered alterations in RNA granule distributions and associated neuronal substates prior to measurable neuronal loss, highlighting potential therapeutic targets for early AD pathology.

bioinformatics↗

bioRxiv2025

Active Learning for Protein Structure Prediction

Accurate protein structure prediction is challenging especially for families and types that are not well-represented in current training data. Active learning selects candidates for labeling with the aim of most rapidly improving model performance. In a general, many labeling strategies have been proposed. However, with protein structure prediction, most of these strategies dont apply or are difficult due to the high-dimensional, variable-dimensional regression target and the inherent complexity of the models involved. We applied a novel active learning strategy, DEW-DROP, to protein structure prediction on two different protein datasets: VHH-only antibodies (Nanobodies), and Mycobacterial proteins. We introduce a domain-specific fine-tuned Equifold model for VHH structures and apply DEWDROP to generate ensembles of predictions using Monte Carlo dropout. Using the statistics of these we select batches with high information content for labeling. We show that DEWDROP (1) improves model training efficiency through batch optimization outper-forming baselines, and (2) selects data with relevant high information content.

molecular biology↗

bioRxiv2025

Progressively reduced cerebral oxygen metabolism and elevated plasma NfL levels in the zQ175DN mouse model of Huntington disease

Huntingtons disease (HD) is a progressive neurodegenerative disorder caused by a CAG-repeat expansion in exon-1 of the huntingtin gene. Currently, no disease-modifying therapies are available, with a significant challenge in evaluating therapeutic efficacy before clinical symptoms emerge. This highlights the need for early biomarkers and intervention strategies. Therefore, it is essential to develop and characterize accurate mouse models and identify early biomarkers for preclinical therapeutic development. In this study, we characterized the pathological progression of the heterozygous zQ175 neo-deleted knock in (zQ175DN) mouse model across four age groups: 3, 6, 10, and 16 months to identify human translatable outcome measures. T2-relaxation-under-spin-tagging (TRUST) MRI was used to assess global CMRO2, while T2-weighted MRI was used to analyze brain volumes. Significant brain volume loss was detected as early as 6 months of age, worsening progressively with age in the zQ175 DN mice, resembling HD brain volumetric changes. A decline in CMRO2 was observed in 6-month-old zQ175 DN mice, with significant and progressive reductions in 10- and 16-months old HD mice. Additionally, PHP1-positive mutant huntingtin (mHTT) aggregates were present in the striatum of zQ175 DN mice at all four age groups, with intranuclear localization prior to 6 months, transitioning to both intranuclear and neuropil aggregates in older zQ175 DN mice, suggesting that the localization of mHTT aggregates may reflect the severity of HD pathogenesis. Interestingly, plasma neurofilament light chain (NfL) protein concentrations were significantly elevated at 6 months of age and older zQ175DN mice. These findings provide valuable insights for selecting outcome measures in preclinical evaluations of HD therapies using the zQ175 DN mouse model.

neuroscience↗

bioRxiv2025

clusIBD: Robust Detection of Identity-by-descent (IBD) Segments Using Unphased Genetic Data from Poor-quality DNA Samples

Inferring relatedness through the detection of identity-by-descent (IBD) segments is widely used in many fields. However, existing methods are often powerless for poor-quality DNA samples. Here, we propose a method, clusIBD, which can robustly detect IBD segments using unphased genetic data with high genotype errors. We evaluated and compared the performance of clusIBD with IBIS, TRUFFLE, and IBDseq using simulated data, artificial poor-quality materials and ancient DNA samples. The results showed that clusIBD outperformed these state-of-the-art existing tools and may be a promising tool for kinship inference in fields such as ancient DNA analysis and criminal investigation (freely available at https://github.com/Ryan620/clusIBD/).

genetics↗

bioRxiv2025

CHIEF: An Attention-based Ensemble Learning Framework for Functional Protein Design

Protein de novo design is a longstanding challenge in biological field due to the multifaceted physicochemical properties and complexities of proteins. Several deep learning models have emerged for protein de novo design. However, each model exhibits distinct strengths and limitations because of the differences in training strategies or neural network architectures. Therefore, improving the effectiveness of protein design, particularly for functional protein, requires further improvement. To tackle this challenge, we developed CHIEF (Chimera Ensemble Inverse Folding), an attention-based ensemble framework that integrates five pretrained base models (ProteinMPNN-vanilla, ProteinMPNN-soluble, ESM-IF, Frame2seq and PiFold) to leverage their complementary strengths and mitigate limitations. Compared with the base models, CHIEF significantly improved the sequence recovery rate by 16.6-28.0%, while reducing the prediction perplexity by 22.7-34.6%. CHIEF also exhibited superior protein-designing capacity in variable sequence- and structure-based metrics and in large and complex proteins. CHIEF dynamically captured the semantic information from base models in a context-dependent manner and was minimally affected by the ablation of each base model. More importantly, CHIEF demonstrates real-world applicability to design functional malate dehydrogenase (MDH), achieving a 100% success rate. In summary, our study develops an ensemble deep learning model that improves the efficacy of protein sequence design, and will be a valuable platform for protein engineering and drug development.

bioengineering↗

bioRxiv2025

Murine Leukemia Virus GlycoGag Antagonizes SERINC5 via ER-phagy Receptor RETREG1

Serine incorporator 5 (SERINC5) is a host restriction factor that targets certain enveloped viruses, including human immunodeficiency virus type 1 (HIV-1) and murine leukemia virus (MLV). It integrates into the viral envelope from the cell surface, inhibiting viral entry. SERINC5 is transported to the cell surface via polyubiquitination, while a single K130R mutation retains it in the cytoplasm. Both HIV-1 Nef and MLV glycoGag proteins antagonize SERINC5 by reducing its expression in producer cells. Here, we report that MLV glycoGag employs selective autophagy to downregulate SERINC5, demonstrating a more potent mechanism for decreasing its cell surface expression. Although glycoGag is a type II integral membrane protein, it primarily localizes to the cytoplasm and undergoes rapid proteasomal degradation. Employing the K130R mutant, we show that Nef, primarily associated with the plasma membrane, downregulates SERINC5 only after it has trafficked to the cell surface, whereas glycoGag can reduce its expression before reaching the plasma membrane while still in the cytoplasm. Nonetheless, an interaction with SERINC5 stabilizes and recruits glycoGag to the plasma membrane, enabling it to downregulate SERINC5 from the cell surface. Through affinity-purified mass spectrometry analysis combined with CRISPR/Cas9 knockouts, we find that glycoGags activity depends on reticulophagy regulator 1 (RETREG1), an ER-phagy receptor. Further knockout experiments of critical autophagy genes demonstrate that glycoGag downregulates cytoplasmic SERINC5 via micro-ER-phagy. These findings provide crucial new insights into the ongoing arms race between retroviruses and SERINC5 during infection. AUTHOR SUMMARYHIV-1 Nef and MLV glycoGag are unrelated viral proteins, yet both counteract the same host restriction factor, SERINC5, to facilitate productive infection. In this study, we report a novel pathway through which glycoGag downregulates SERINC5. We demonstrate that while Nef downregulates SERINC5 only after it has trafficked to the cell surface, glycoGag can directly downregulate SERINC5 in the cytoplasm before it reaches the plasma membrane. Furthermore, we show that this pathway is mediated by the ER-phagy receptor RETREG1, which targets SERINC5 for degradation via micro-ER-phagy. This mechanism provides a more effective means of blocking SERINC5 antiviral activity. These findings reveal that retroviruses have evolved different strategies to antagonize SERINC5, highlighting the critical role of SERINC5 in restricting retroviral infections.

microbiology↗

bioRxiv2025

Chromosome-level genome assemblies of five Sinocyclocheilus species

Sinocyclocheilus, a genus of tetraploid fishes, is endemic to the karst regions of Southwest China. All species within this genus are classified as second-class national protected species due to their unique and fragile habitat. However, absence of high-quality genomic resources has hindered various research efforts to elucidate their phylogenetic relationships and the origin of polyploidy. To address these academic challenges, we at first constructed a high-quality genome assembly for the most abundant representative, golden-line barbel (Sinocyclocheilus grahami), by integration of PacBio long-read and Hi-C sequencing technologies. The final scaffold-level genome assembly of S. grahami is 1.6 Gb in length, with a scaffold N50 up to 30.7 Mb. A total of 42,205 protein-coding genes were annotated. Subsequently, 93.1% of the assembled genome sequences (about 1.5 Gb) and 93.8% of the total predicted genes were successfully anchored onto 48 chromosomes. Furthermore, we obtained chromosome-level genome assemblies for four other Sinocyclocheilus species (including S. anophthalmus, S. maitianheensis, S. anshuiensis, and S. rhinocerous) based on homologous comparison. These genomic data we present in this study provide valuable genetic resources for in-depth investigation on cave adaptation and improvement of economic values and conservation of diverse Sinocyclocheilus fishes.

genomics↗

bioRxiv2025

Pediatric cerebrospinal fluid immune profiling distinguishes pediatric-onset multiple sclerosis from other pediatric-onset acute neurological disorders

The cerebrospinal fluid (CSF) provides a unique glimpse into the central nervous system (CNS) compartment and offers insights into immune processes associated with both healthy immune surveillance as well as inflammatory disorders of the CNS. The latter include demyelinating disorders, such as multiple sclerosis (MS) and myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD), that warrant different therapeutic approaches yet are not always straightforward to distinguish on clinical and imaging grounds alone. Here, we establish a comprehensive phenotypic landscape of the pediatric CSF immune compartment across a range of non-inflammatory and inflammatory neurological disorders, with a focus on better elucidating CNS-associated immune mechanisms potentially involved in, and discriminating between, pediatric-onset MS (MS) and other pediatric-onset suspected neuroimmune disorders, including MOGAD. We find that CSF from pediatric patients with non-inflammatory neurological disorders is primarily composed of non-activated CD4+ T cells, with few if any B cells present. CSF from pediatric patients with acquired inflammatory demyelinating disorders is characterized by increased numbers of B cells compared to CSF of both patients with other inflammatory or non-inflammatory conditions. Certain features, including particular increased frequencies of antibody-secreting cells (ASCs) and decreased frequencies of CD14+ myeloid cells, distinguish MS from MOGAD and other acquired inflammatory demyelinating disorders.

immunology↗

bioRxiv2025

Resistance to Radiation Enhances Metastasis by Altering RNA Metabolism

The cellular programs that mediate therapy resistance are often important drivers of metastasis, a phenomenon that needs to be understood better to improve screening and treatment options for cancer patients. Although this issue has been studied extensively for chemotherapy, less is known about a causal link between resistance to radiation therapy and metastasis. We investigated this problem in triple-negative breast cancer (TNBC) and established that radiation resistant tumor cells have enhanced metastatic capacity, especially to bone. Resistance to radiation increases the expression of integrin {beta}3 (ITG{beta}3), which promotes enhanced migration and invasion. Bioinformatic analysis and subsequent experimentation revealed an enrichment of RNA metabolism pathways that stabilize ITG{beta}3 transcripts. Specifically, the RNA binding protein heterogenous nuclear ribonucleoprotein L (HNRNPL), whose expression is regulated by Nrf2, mediates the formation of circular RNAs (circRNAs) that function as competing endogenous RNAs (ceRNAs) for the family of let-7 microRNAs that target ITG{beta}3. Collectively, our findings identify a novel mechanism of radiation-induced metastasis that is driven by alterations in RNA metabolism.

cancer biology↗

bioRxiv2025

Single-cell RNA-seq reveals altered plasma cell subsets and decreased cytotoxicity of NK cells in patients with Kawasaki diseas

AimThe pathogenesis and therapeutic strategies of Kawasaki disease (KD) are worth further exploring. Using single-cell RNA sequencing (scRNA-seq), our study aimed to explore the landscape of peripheral blood mononuclear cells (PBMCs) in patients with KD. MethodsWe analyzed the scRNA-seq data of three patients with KD and three healthy controls from the GSE168732 dataset. Additionally, we explored the immune profiles and immune cell subtypes of patients with KD. ResultsSignificantly increased B cells and decreased NK cells were observed in the KD group compared with that in the control group. Furthermore, six B cell subsets were identified in the PBMCs of patients with KD. Particularly, plasma cells (CD9+ and S100A9+ B cell clusters) distinctly increased in the KD group. CD9+ B cell cluster was characterized by vascular endothelial growth factor (VEGF) signaling-associated marker genes and DEGs. Meanwhile the S100A9+ B cell cluster was characterized by platelet aggregation marker genes. As for NK cells, CD16+CD56dim NK cells were enriched in the KD group. Cytotoxicity-related activating receptors (KLRD1,KLRC3) and cytotoxicity-associated genes (PRF1, NKG7, GZMA, GZMH, GNLY) were downregulated in the KD group. ConclusionCD9+ and S100A9+ plasma cells may contribute to CALs in KD by upregulating VEGF and activating platelet. In addition, decreased cytotoxicity of NK cells mediated by KLRD1/KLRC3 receptor may play a vital role in the development of KD. Our results suggested that plasma cells and NK cells could be promising targets for the treatment of KD.

immunology↗

bioRxiv2025

Multi-omic Characterization of HIV Effects at Single Cell Level across Human Brain Regions

HIV infection exerts profound and long-lasting neurodegenerative effects on the central nervous system (CNS) that can persist despite antiretroviral therapy (ART). Here, we used single-nucleus multiome sequencing to map the transcriptomic and epigenetic landscapes of postmortem human brains from 13 healthy individuals and 20 individuals with HIV who have a history of treatment with ART. Our study spanned three distinct regions--the prefrontal cortex, insular cortex, and ventral striatum--enabling a comprehensive exploration of region-specific and cross-regional perturbations. We found widespread and persistent HIV-associated transcriptional and epigenetic alterations across multiple cell types. Detailed analyses of microglia revealed state changes marked by immune activation and metabolic dysregulation, while integrative multiomic profiling of astrocytes identified multiple subpopulations, including a reactive subpopulation unique to HIV-infected brains. These findings suggest that cells from people with HIV exhibit molecular shifts that may underlie ongoing neuroinflammation and CNS dysfunction. Furthermore, cell-cell communication analyses uncovered dysregulated and pro-inflammatory interactions among glial populations, underscoring the multifaceted and enduring impact of HIV on the brain milieu. Collectively, our comprehensive atlas of HIV-associated brain changes reveals distinct glial cell states with signatures of pro-inflammatory signaling and metabolic dysregulation, providing a framework for developing targeted therapies for HIV-associated neurological dysfunction.

bioinformatics↗

bioRxiv2025

Principled PCA separates signal from noise in omics count data

Principal component analysis (PCA) is indispensable for processing high-throughput omics datasets, as it can extract meaningful biological variability while minimizing the influence of noise. However, the suitability of PCA is contingent on appropriate normalization and transformation of count data, and accurate selection of the number of principal components; improper choices can result in the loss of biological information or corruption of the signal due to excessive noise. Typical approaches to these challenges rely on heuristics that lack theoretical foundations. In this work, we present Biwhitened PCA (BiPCA), a theoretically grounded framework for rank estimation and data denoising across a wide range of omics modalities. BiPCA overcomes a fundamental difficulty with handling count noise in omics data by adaptively rescaling the rows and columns - a rigorous procedure that standardizes the noise variances across both dimensions. Through simulations and analysis of over 100 datasets spanning seven omics modalities, we demonstrate that BiPCA reliably recovers the data rank and enhances the biological interpretability of count data. In particular, BiPCA enhances marker gene expression, preserves cell neighborhoods, and mitigates batch effects. Our results establish BiPCA as a robust and versatile framework for high-throughput count data analysis.

bioinformatics↗

bioRxiv2025

DAZAP2 functions as a pan-coronavirus restriction factor by inhibiting viral entry and genomic replication

The SARS-CoV-2 pandemic and the emergence of novel variants underscore the need to understand host-virus interactions and identify host factors that restrict viral infection. Here, we perform a genome-wide CRISPR knockout screen to identify host restriction factors for SARS-CoV-2, revealing DAZAP2 as a potent antiviral gene. DAZAP2, previously implicated in SARS-CoV-2 restriction, is found to inhibit viral entry by blocking virion fusion with both endolysosomal and plasma membranes. Additionally, DAZAP2 suppresses genomic RNA replication without affecting the primary translation of viral replicases. We demonstrate that DAZAP2 functions as a pan-coronavirus restriction factor across four genera of coronaviruses. Importantly, knockout of DAZAP2 enhances SARS-CoV-2 infection in mouse models and in human primary airway epithelial cells, confirming its physiological relevance. Mechanistically, antiviral activity of DAZAP2 appears to be indirect, potentially through the regulation of host gene expression, as it primarily localizes to the nucleus. Our findings provide new insights into the host defense system against coronaviruses and highlight DAZAP2 as a potential target for host-directed antiviral therapies. IMPORTANCEDuring viral infection, the host defense response is mediated by a variety of host factors through distinct mechanisms that have yet to be fully elucidated. Although DAZAP2 was previously implicated in SARS-CoV-2 restriction, its mechanisms of action and in vivo relevance remain unclear. In this study, we identify the DAZAP2 as a potent pan-coronavirus restriction factor that inhibits viral infection through dual mechanisms: blocking virion fusion with both endolysosomal and plasma membranes, and suppressing genomic RNA replication. We confirm its physiological relevance in host defense using mouse models and primary cell cultures. This study advances our understanding of host-pathogen interactions. Targeting DAZAP2 or its regulatory pathways could provide a new approach to enhance host defense against current and future coronavirus threats.

microbiology↗

bioRxiv2025

Engineered spermidine-secreting Saccharomyces boulardii enhances olfactory memory in Drosophila melanogaster

The polyamines putrescine, spermidine and spermine are ubiquitous metabolites synthesized in all cells. The intracellular levels of polyamines, especially spermidine, decrease in aging. Oral spermidine supplementation has been reported to alleviate aspects of age-related disease in animal models, including decline in learning and memory. The diverse health benefits of spermidine supplementation, often at doses that do not significantly alter spermidine levels of target organs, suggests that exogenous spermidine may have a common site of action, the gastrointestinal (GI) tract. To directly deliver spermidine to the GI tract with minimum impact on the global spermidine levels, we engineered the probiotic yeast Sacchromyces boulardii (Sb) to overproduce and secrete spermidine. We tested the effects of a spermidine-producing yeast strain (Sb576) on age-associated learning and memory decline in an olfactory classical conditioning in Drosophila melanogaster. Feeding of newly emerged adult flies [w1118(isoCJ1)] for 30 days with food supplemented with live Sb576, but not live wild-type Sb (SbWT) or free spermidine, reduced age-associated short-term memory (STM) decline. Notably, Sb576 supplementation, but not SbWT or spermidine supplementation, of either young flies or old flies for only three days also enhanced STM without affecting locomotive ability. Transcriptome analysis of the gut revealed relatively few (30) differentially overexpressed genes in the Sb576 group compared to the SbWT group including the gene coding neuropeptide Dh31, which has been implicated in memory in the flies. These results demonstrate that in situ production of spermidine by a synthetic biotic yeast in the GI tract can enhance STM, and further suggest a mechanism involving the gut-brain axis.

synthetic biology↗

bioRxiv2025

Comparative Analysis of Phytochemical Constituents of Ginkgo Biloba Flowers and Leaves, and Evaluation of Their Biological Activities

BackgroundsGinkgo biloba L. has attracted much attention for its unique chemical composition and pharmacological properties, and most of the research focused on Ginkgo biloba leaves (GBL). Our preliminary research found that Ginkgo biloba flowers (GBF) were superior to GBL in terms of anti-radiation activity, but the underlying cause of this discrepancy in activity remains elusive. ObjectivesThe aim of this study was to systematically compare the chemical and nutritional composition of Ginkgo biloba flowers and leaves, to further elucidate the material basis of the medicinal and nutritional value of Ginkgo biloba flowers, and to conduct further comparative studies on the anti-ferroptosis activity and anti-radiation activity of the two. MethodsIn this study, the chemical constituents of GBF and GBL were identified by UPLC-Q-orbitrap HRMS, and the contents of amino acids, fatty acids, inorganic elements, purines, and ceramides of both were determined. Meanwhile, the anti-iron death activity and anti-radiation activity of GBF and GBL were comparatively studied by cellular experiments. ResultsThe results showed that the content of chemical components such as flavonoids and other nutrients such as amino acids, fatty acids, and ceramides were richer in GBF than in GBL, and GBF was indeed superior to GBL in terms of anti-radiation and anti-ferroptosis activity. ConclusionThrough in-depth analyses of the chemical and nutritional compositions of Ginkgo biloba flowers and leaves, the present study reveals the possible material basis for the stronger activity of GBF and provides theoretical support for its application in nutraceuticals and pharmaceuticals, especially in the development of functional nutraceuticals and anti-radiation drugs with higher health benefits.

biochemistry↗

bioRxiv2025

High-speed mapping of whole-mouse peripheral nerves at subcellular resolution

In contrast to the rapid advancements in mesoscale connectomic mapping of the mammalian brain, similar mapping the peripheral nervous system has remained challenging due to the bodys size and complexity. Here, we present a high-speed blockface volumetric imaging system with an optimized workflow of whole-body clearing, capable of imaging the entire adult mouse at micrometer resolution within 40 hours. Three-dimensional reconstruction of individual spinal fibers in Thy1-EGFP mice reveals distinct morphological features of sensory and motor projections along the ventral and dorsal rami. Immunostaining facilitates body-wide mapping of sympathetic nerves and their branches, highlighting their perivascular patterns in limb muscles, bones, and most visceral organs. Viral tracing elucidates the fine architecture of vagus nerves and individual vagal fibers, revealing unexpected projection routes to various organs. Our approach offers an effective means to achieve a holistic understanding of cellular-level interactions among different systems that underlie body physiology and disease. HighlightsO_LIImaging of whole adult mouse at uniform subcellular resolution within 40 hours C_LIO_LIReconstruction of 191 thoracic spinal neuron projections for Thy1-EGFP mice C_LIO_LIMapping of immunolabeled sympathetic projections and their perivascular patterns C_LIO_LIResolving virus-labeled architecture of vagus nerves and complex single-fiber routes C_LI

neuroscience↗

bioRxiv2025

Inhibition of cytosolic translation mitigates mitochondrial dysfunction in C. elegans

The mitochondrial unfolded protein response (UPRmt), which promotes mitochondrial proteostasis and biogenesis is regulated by the transcription factor ATFS-1. In C. elegans, impaired atfs-1 expression perturbs mitochondrial function and slows development. Here, via an RNAi suppressor screen, we found that inhibition of the nuclear hormone receptor NHR-180 increases mitochondrial function and the rate of development in atfs-1(null) worms. NHR-180 is activated during mitochondrial dysfunction and induces transcription of genes required for protein synthesis on cytosolic and mitochondrial ribosomes. Importantly, the NHR-180 ligand binding domain interacts with AMP, which results in increased protein synthesis potentially to promote mitochondrial biogenesis and recovery from transient mitochondrial perturbations. However, NHR-180 exacerbates the mitochondrial dysfunction caused by mutations in genes required for oxidative phosphorylation. Consistent with these findings, we found that inhibition of the S6 kinase homolog RSKS-1 also increased mitochondrial function in atfs-1(null) worms. Importantly, treatment with an S6 kinase inhibitor also increased respiration and mtDNA content in mammalian ATF5-knockout cells and OXPHOS-deficient models, suggesting that translation regulation is a conserved, targetable approach for restoring mitochondrial function in disease.

developmental biology↗

bioRxiv2025

A comprehensive quality control pipeline in human microbiome research for large population studies

The widespread application of high-throughput Next Generation Sequencing (NGS) technologies has made microbiome research an emerging field in public health and biomedical sciences. However, there are still many challenges that need to be addressed in this field. Pipelines available to generate microbiome data across cohorts are diverse, and sources of variation to be recorded and evaluated during microbiome profiling have not been standardized. Moreover, meticulous quality control of the microbiome data processing, from collection to computational quantification is still challenging, especially in large population studies. Innovative approaches are required to handle samples and to minimize the potential bias introduced by logistic hurdles in biobanking. In this paper, we describe the methodological steps surrounding the optimization of the 16S rRNA gut microbiome profiling in two large prospective cohorts the Generation R Study (mean age 9.83 {+/-} 0.32 years) and the Rotterdam Study (mean age 62.67 {+/-} 5.66 years). This paper also highlights potential solutions to sample mislabeling in large-scale microbiome analysis. To summarize, our study addresses common problems in human microbiome research. It aims to improve the research quality and reliability by integrating more stringent quality control standards into microbiome research.

bioinformatics↗