Biology subjects

Ni, Y.

Publications and source records attributed to Ni, Y..

At least 19 recordsLinked to original sources

bioRxiv2026

SCG: Spatially Co-Expressed Gene Identification through Spatially Varying Networks

Spatial transcriptomics has enabled the advancement of gene expression analysis, yet spatial co-expression remains understudied. We introduce spatial covariance regression (SCR), a scalable Bayesian factor-model-based framework for estimation of spatially-resolved gene co-expression networks across tissue domains. These networks provide the spatial map of gene-gene correlations and enable the identification of spatially co-expressed genes (SCGs), which serve as potential prognostic biomarkers and therapeutic targets.

genomics↗

bioRxiv2026

Spatial multi-omics analysis reveals vimentin-high macrophages-endothelial cells niche shapes CAFs heterogeneity in colorectal cancer metastasis

The spatial architecture of the tumor microenvironment (TME) is pivotal in the progression of colorectal cancer (CRC) liver metastasis. By applying high-plex spatial multi-omic mapping and neighborhood analysis to a discovery cohort of colorectal cancer primary tumor (PT) and paired liver metastases (LM), we identified a specialized vimentin-high macrophages-endothelial cells niche that orchestrates cancer-associated fibroblast (CAF) phenotypes. Mechanistically, in primary tumors, vimentin-high macrophages secrete INHBA to activate the ACVR2/TGF-{beta} axis in endothelial cells, driving CAFs toward a myCAF phenotype. Conversely, in liver metastases, these macrophages secrete CXCL9 to trigger the PI3K-Akt/NF-[kcy]B/CXCL12 cascade in endothelial cells, directing CAFs toward an iCAF state. Clinically, high niche activity predicts poor survival. Divergent endothelial signaling in primary versus metastatic lesions exposes site-specific stromal vulnerabilities for therapeutic targeting, with architectural features discernible from routine histopathology. These findings reveal a site-specific regulatory mechanism of the macrophage-endothelial niche, offering a novel and clinically significant biomarker for CRC prognosis.

cancer biology↗

bioRxiv2026

Establishing a Retron-Based Cytosine Base Editor for Targeted Hypermutation in Escherichia coli

Current cytosine base editors (CBEs) are limited to unidirectional C to T conversions, restricting their applications. Retrons, bacterial genetic elements, encode a reverse transcriptase that generates multicopy single-stranded DNA (msDNA) by reverse transcribing specific non-coding RNA (ncRNA). This msDNA mimics Okazaki fragments during DNA replication, making retrons promising for gene editing. Here, we developed a retron-based cytosine base editor (RCBE) by fusing cytosine deaminase with reverse transcriptase (RT-CDA) within the retron system. RCBE first transcribes ncRNA, allowing RT-CDA to deaminate cytosine on the ncRNA. The modified ncRNA is then reverse transcribed into msDNA, where RT-CDA induces further cytosine deamination. This mutant msDNA introduces specific mutations into target gene sequences, enabling both C to T and G to A conversions. Using RCBE, we demonstrated accelerated molecular evolution of the rpoB gene in Escherichia coli. High-throughput sequencing confirmed that RCBE achieves a mutation rate of up to 0.2% in regions with high GC content. Our findings establish RCBE as a versatile tool, particularly suitable for directed evolution in GC-rich regions, with broad potential applications across various bacterial and eukaryotic hosts.

Synthetic Biology↗

bioRxiv2026

RT-nested and interfering-Primer PCR reveal prevalent isoform-specific A-to-I RNA editing in neuronal genes

BackgroundMetazoan adenosine-to-inosine (A-to-I) mRNA editing temporospatially diversifies the neuronal transcriptome and proteome. The limited read length from next-generation sequencing (NGS) constrains the quantification of the potentially differential editing levels across different splicing isoforms, restricting our understanding of the extent to which RNA editing contributes to molecular diversity and its interplay with splicing. MethodsWe employed reverse transcription nested PCR (RT-nPCR) and developed a novel interfering-Primer PCR (iPrimer PCR) technique to distinguish different transcripts of any gene. We selected multiple essential genes exhibiting RNA editing in coding sequences (CDSs) or untranslated regions (UTRs) for isoform-specific amplification and Sanger sequencing. ResultsNine different Adar isoforms together with pre-mRNA had distinct editing levels at the S>G auto-recoding site, which was predicted to have isoform-specific effects on catalytic activities. Although pre-mRNA editing might exert isoform-dependent promotion/suppression of splicing, closely located editing sites, such as those in neuronal genes qvr and stj, still exhibited high correlation in editing levels due to co-editing. iPrimer strategy further discovered differential recoding levels between the long/short 3UTR isoforms of gene jef. ConclusionsWe provide the first comprehensive solution for isoform-specific PCR amplification of any gene, enabling quantification of RNA editing level of different isoforms. Our results offer insights into how RNA editing interplays with splicing, and highlight its complicated role in expanding molecular diversity. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=79 SRC="FIGDIR/small/725286v1_ufig1.gif" ALT="Figure 1"> View larger version (17K): org.highwire.dtl.DTLVardef@3c4e61org.highwire.dtl.DTLVardef@13def88org.highwire.dtl.DTLVardef@138fa91org.highwire.dtl.DTLVardef@1ca7460_HPS_FORMAT_FIGEXP M_FIG C_FIG We developed isoform-specific PCR followed by Sanger sequencing, and achieved the quantification of differential RNA editing levels in different transcripts of a gene.

molecular biology↗

bioRxiv2026

Integrated Metagenomics and Metabolomics Studies Reveal Core Bacterial Guild Regulating Carbohydrate Metabolism in Pediatric MASLD

BackgroundMetabolic dysfunction-associated steatotic liver disease (MASLD) is a prevalent pediatric disorder with limited treatment options, primarily due to an incomplete understanding of its molecular drivers. Recent research underscores the role of microbial guilds in metabolic health, but the mechanisms by which dysbiosis driven by core species and co-abundant symbionts disrupt metabolic homeostasis in pediatric MASLD remain unclear. ResultsHere, we conducted integrated metagenomic and metabolomic analyses on 285 pediatric subjects including MASLD patients, obese and healthy controls. The gut dysbiosis in MASLD was characterized by a depletion of Phocaeicola vulgatus, Bacteroides uniformis, Parabacteroides distasonis, and Bacteroides thetaiotaomicron. Co-abundance network analysis, integrating our cohort with four public datasets, identified these species as core guild members associated with MASLD. Microbial enrichment analysis showed significant disruptions in carbohydrate metabolism, particularly the downregulation of the tricarboxylic acid (TCA) cycle, fructose and sucrose metabolism, and pentose and glucuronate interconversions. P. vulgatus and B. uniformis were identified as dominant species linked to the downregulation of KEGG orthologs (KOs) in these disrupted pathways that were inversely correlated with hepatic injury biomarkers. CAZyme database analysis further emphasized P. vulgatus as the primary contributor to glycoside hydrolases involved in monosaccharide utilization. Finally, both untargeted and targeted metabolomics analysis validated a disrupted metabolic network centered on the TCA cycle and monosaccharide metabolism in pediatric MASLD. ConclusionOur findings suggest the core guild species P. vulgatus and B. uniformis may serve as critical regulators of carbohydrate metabolism in pediatric MASLD, offering potential mechanistic targets for gut microbiome-based interventions.

microbiology↗

bioRxiv2026

Metabolic specialization structures gut bacterial niches and drives colorectal cancer progression

Despite the established association between the gut microbiome and colorectal cancer (CRC), the functional distinction between microbial passengers and drivers of CRC progression remains unresolved. Here, we collected stool, blood, as well as paired tumor, and normal mucosa tissues from seventy-seven CRC patients to characterize the systemic and localized impact of the gut microbiome on early- and late-stage CRC. By deep shotgun metagenomic sequencing, we identified distinct bacterial species and functions residing in tumor versus normal mucosa, highlighting an enrichment of oral-associated bacteria in tumor tissues. Several of these species remained undetected in the stool microbiome analysis. We further combined bacterial culturing with untargeted metabolomics of bacteria enriched in tumor and normal mucosa tissues, revealing distinct clusters of metabolic potential. Functional testing of multiple members from one cluster comprising both tumor- and mucosa-enriched species revealed Leptotrichia wadei as a pro-tumorigenic bacterium in a murine CRC model. Single-nucleus RNA sequencing and in vitro experiments further demonstrated that L. wadei and its secretome induces M2 macrophage polarization to promote tumor growth. Overall, our study shows that metabolic specialization structures microbial colonization niches, while species-specific metabolic outputs identify functional drivers of CRC progression, and uncovers L. wadei as an oncogenic bacterium in CRC.

microbiology↗

bioRxiv2026

When CycloneSEQ meets Oxford Nanopore Technologies: a performance comparison of contemporary nanopore DNA sequencing platforms

Nanopore sequencing enables direct analysis of native DNA modifications, but these modifications can also introduce systematic basecalling errors. Here, we investigated how bacterial DNA methylation contributes to nanopore substitution errors using matched native whole-genome sequencing (WGS) and methylation-depleted whole-genome amplification (WGA) datasets from six bacterial species across CycloneSEQ (CS) and Oxford Nanopore Technologies platforms (ONT). Adenine-to-guanine (A2G) and guanine-to-adenine (G2A) substitutions were consistently enriched across species, nanopore platforms, sequencing configurations, and basecalling models, indicating a shared nanopore-associated substitution bias. This enrichment remained detectable in WGA reads, whereas native WGS reads showed a further increase. Using independent PacBio methylation profiling, we found that the WGS-associated substitution excess was strongly concentrated around bacterial methylation motifs and was minimal in non-motif regions. The magnitude and substitution pattern of these errors varied among motifs and sequencing platforms. At a subset of motif-associated positions, alternative-base fractions exceeded 50%, producing SNP-like signals. In ONT data, 28 WGS-specific calls survived the applied SNP-calling filters, all within PacBio-supported methylation contexts, and most showed significant strand imbalance. Together, these results identify a shared A2G/G2A substitution bias in all nanopore datasets and support a methylation-associated increase in these errors near bacterial methylation motifs, with some loci producing SNP-like artifacts.

bioinformatics↗

bioRxiv2025

Mitochondrial Integrated Stress Response Activation Creates a Therapeutic Vulnerability to MCL-1 Inhibition in Acute Myeloid Leukemia

MCL-1 (myeloid cell leukemia-1) promotes survival and confers therapeutic resistance in acute myeloid leukemia (AML), particularly in high-risk subtypes harboring KMT2A rearrangements (KMT2A-r). Clinical trials of patients with hematological malignancies treated with MCL-1 inhibitor monotherapy have revealed dose-limiting toxicity and poor response rates. Therefore, we sought to identify combinatorial treatment approaches to enhance the efficacy of MCL-1 inhibitors with the goal of improving response rates and limiting toxicities. Here, we report the inhibition of electron transport chain (ETC) complex I (CI) function as a synthetic lethal partner for MCL-1 inhibition. Co-targeting CI and MCL-1 synergistically reduces the viability in AML cell lines and patient-derived xenograft (PDX) samples in vitro, while significantly prolonging survival in mice bearing PDX AML, indicating the preclinical potential for combinatorial therapy. These findings provide a mechanistic rationale and preclinical evidence for dual inhibition of MCL-1 and CI as a therapeutic strategy, offering a potential path to overcome resistance to single-agent MCL-1 inhibitors and improve outcomes for patients with high-risk AML. Mechanistically, we reveal that CI inhibition induces the activation of the integrated stress response (ISR), resulting in ATF4 activation downstream of the eIF2 kinase, HRI. The activation of HRI by CI inhibition is dependent on the mitochondrial stress messenger, DELE1. Together, these results indicate that co-inhibition of MCL-1 and ETC CI function has the potential for improving responses in patients with KMT2A-r AML.

cancer biology↗

bioRxiv2025

Acoustic Coupling for Double-Blind Human Low-Intensity Focused Ultrasound Neuromodulation

ObjectiveLow-intensity focused ultrasound (LIFU) is a non-invasive neuromodulation technique with the potential for precise targeting of small and deep human brain circuitry. To ensure rigorous and reproducible effects, it is necessary to implement double-blinding to mitigate potential experimental biases. This study innovates on previous ultrasound coupling methods by embedding a 3D-printed thermoplastic disc in a high-density gel-polymer matrix to create identical gel-plastic coupling devices that either transmit (verum) or block (sham) ultrasound. MethodsWe evaluated varying thicknesses (1.5 mm, 2,0 mm, 2.5 mm) and infill densities (25%, 50%, 75%, and 100%) of Acrylonitrile Butadiene Styrene (ABS) for insertion loss and effects on beam characteristics across relevant human neuromodulation frequencies from 0.2 - 1 MHz. ResultsABS at 1.5 mm thickness and 50 % infill had the lowest insertion loss at 0.50 MHz of 0.9 {+/-} 0.04 dB demonstrating acoustic transparency suitable for a verum device. For the sham device, we introduced an internal air gap that produced 31 dB insertion loss at 0.50 MHz. The verum device demonstrated minimal effects on the beam shape with a radial peak shift of 0.3 {+/-} 0.2 mm and an average axial shift of 0.5 mm. DiscussionThis novel gel-plastic coupling device can be tailored to most LIFU transducer shapes and is designed to support double-blind protocols by maintaining visual and tactile indistinguishability while controlling transmitted energy. This method provides a cost-effective and easily implementable solution for double-blinding in human LIFU studies to improve the reliability and rigor of experimental outcomes.

neuroscience↗

bioRxiv2025

T-PGI: an engineered STITCHR system for scarless, programmable genome integration

Scarless, programmable insertion of defined DNA remains a central goal for therapeutic genome editing. We introduce T-PGI (Transposon-mediated programmable genomic integration), an engineered implementation of STITCHR that preserves target-primed reverse transcription (TPRT) while substantially improving efficiency, specificity, and modularity. T-PGI uses R2Tocc, a low-background ortholog that we further engineered through defined deletions, rational point mutations, and modular domain insertions to enhance performance. The system employs paired nCas9 nicks flanking homology arms and bicistronic co-expression with dual NLSs, together with optimized RNA donor designs. Using combinatorial guide-template screening, T-PGI achieves robust integration across diverse cargos, including precise cassette insertion following multi-kilobase deletions. Short- and long-read sequencing confirm high-fidelity insertion with minimal local indels or structural variants. Collectively, these advances establish T-PGI as a practical and adaptable platform for accurate, scarless genome integration and provide concise design principles spanning enzyme architecture, donor configuration, and guide pairing for next-generation therapeutic editing.

bioengineering↗

bioRxiv2025

Constructing Gene Regulatory Network using Chatterjee's Rank Correlation with Single-cell Transcriptomic Data

Discovering gene regulatory networks (GRNs) from single-cell RNA sequencing (scRNA-seq) data is critical for understanding cellular function. Still, existing methods are limited by strong theoretical assumptions or high computational complexity. We introduce a multiple testing framework for GRN construction using Chatterjee's rank correlation coefficient, a nonparametric measure of dependence. Our approach overcomes the limitations of traditional methods while offering a transparent, scalable, and computationally efficient alternative to recent black-box machine learning models. Crucially, to address the non-independence of cellular observations inherent to scRNA-seq, we develop a data-driven algorithm for estimating robust testing cutoffs. Furthermore, we exploit the asymmetric nature of Chatterjee's correlation to propose a new test for active regulation, enabling the construction of biologically meaningful and directionally informed GRNs. We demonstrate that our method matches or outperforms state-of-the-art approaches in recovering true gene-gene dependencies and directed regulatory interactions from both simulated and real datasets, particularly for complex, non-linear dependencies, providing a powerful tool for dissecting complex GRNs.

bioinformatics↗

bioRxiv2025

ZmCRY1s interact with GL2 in a blue light dependent manner to regulate epidermal wax composition in Zea mays

Cryptochromes (CRYs) are photolyase-like blue-light / ultraviolet-A (UV-A) receptors that regulate diverse aspects of plant growth. Maize (Zea mays), a major crop often grown under high UV-B radiation, possesses four copies of CRY. However, it remains unclear whether the multiple copies of CRY in maize have evolved to improve UV tolerance or to acquire new functions. In this study, CRISPR-Cas9-engineered Zmcry mutants were used to investigate the functions of four cryptochromes (ZmCRYs) in maize. The findings revealed that ZmCRYs play a redundant role in mediating blue light signaling and in inhibiting the elongation of the mesocotyl. The results also demonstrated that ZmCRYs mediated blue light-enhanced UV-B stress tolerance in Zea mays by upregulating the expression of genes involved in UV-B stress tolerance-related metabolites such as phenylpropanoid, flavonoid, and fatty acid biosynthesis. Furthermore, blue light was found to influence both the accumulation and composition of epidermal waxes, suggesting that blue light enhances epidermal wax accumulation for UV-B stress tolerance. Additionally, it was discovered that ZmCRY1 directly interacted with GLOSSY2 (GL2) in a blue light dependent manner to mediate blue light promoted C32 aldehyde accumulation, shedding new light on the enigma of aldehyde-forming. These results highlight the critical roles of ZmCRY1s in mediating blue light regulated epidermal wax biosynthesis and UV-B tolerance in Zea mays.

plant biology↗

bioRxiv2025

Longitudinal single-cell analysis reveals RUNX1T1 as an early driver in treatment-induced neuroendocrine transdifferentiation

Treatment-induced neuroendocrine prostate cancer (t-NEPC) is a lethal form of advanced prostate cancer that can emerge from adenocarcinoma under androgen receptor pathway inhibition, but the tumor-cell states and regulators underlying this transition remain incompletely defined. Here, we analyzed longitudinal single-cell RNA sequencing data from the LTL331/331R patient-derived xenograft model across seven disease stages, comprising 32,269 tumor-cell transcriptomes from treatment-naive adenocarcinoma, post-castration regression, and relapsed NEPC. We identified an AR-low/NE-low intermediate state that emerged after castration and before overt relapse, as well as two transcriptionally distinct terminal NEPC states marked by ASCL1high/FOXA2low and ASCL1low/FOXA2high programs. RUNX1T1 was induced in the intermediate state and remained elevated across both terminal states. RUNX1T1 enhanced NE-associated features and cell viability during enzalutamide treatment in adenocarcinoma cells, whereas its knockdown in NCI-H660 cells reduced NE-associated transcriptional programs, proliferation, and survival and shifted the transcriptome toward an intermediate-like state. Chromatin interactome analysis and co-immunoprecipitation linked RUNX1T1 to G9A/LASP1-containing chromatin repressor complexes. These findings define a temporal framework for treatment-induced NEPC progression and identify RUNX1T1 as an early-induced and sustained regulator of NE lineage transition and maintenance of established NEPC.

cancer biology↗

bioRxiv2025

Gut Microbiota Dysbiosis and Short-chain Fatty Acid alterations in Pediatric New-Onset Type 1 diabetes with Ketoacidosis

ObjectiveDiabetic ketoacidosis (DKA) stands as the most common acute hyperglycaemic complication with a relatively high mortality rate among children diagnosed with type 1 diabetes (T1D). Previous studies have shed light on gut dysbiosis in newly-onset T1D children, but research targeting the gut microbiota and microbial metabolites in patients with DKA remains scarce. MethodsShotgun metagenomic analysis was conducted on fecal samples from 96 newly diagnosed T1D children, including 32 patients who presented with DKA upon admission. Short-chain fatty acids (SCFAs) were quantified using gas chromatography/mass spectrometry (GC/MS). Comparative analyses were performed on the gut microbiome and SCFA levels between DKA and non-DKA subgroups. ResultsGut microbiota composition differed between DKA and non-DKA groups. While alpha-diversity remained consistent, beta-diversity showed marked differences between the two groups, and the phyla Firmicutes and Bacteroidetes exhibited predominance in the DKA group. DKA was associated with increased potential pathogens and a significant depletion of SCFA-producing genera (Anaerobutyricum, Dialister, Ruminococcus, Roseburia, Dorea, and Butyricicoccus), accompanied by reduced SCFA levels. Further correlation analysis revealed strong associations between SCFAs, SCFA-producing microbiota, and disease severity indicators. Propionic acid and butyric acid mediated the association between SCFA-producing bacteria and DKA. ConclusionThis study first reported reductions in SCFAs and SCFA-producing bacteria in the fecal samples of T1D children at DKA onset. Our findings highlight SCFAs and their producers as protective biomarkers of DKA and suggest that targeting gut microbiota and SCFA metabolism may offer a potential therapeutic strategy for DKA. ImportanceWhile gut microbiota imbalances have been linked to type 1 diabetes (T1D), little is known about the role of gut microbes and their metabolites during acute diabetic ketoacidosis (DKA), an acute and life-threatening complication. This study examined the gut microbiome and levels of short-chain fatty acids (SCFAs) in fecal samples from children with new-onset T1D with and without DKA. DKA was characterized by distinct microbial signatures, including increased potential pathogens, a loss of beneficial SCFA-producing bacteria, and consistently lower SCFA levels. These changes closely correlated with indicators of disease severity, and further mediation analysis revealed the role of SCFAs in linking gut microbiota to DKA. These findings suggest that SCFAs and their producers may serve as protective markers for DKA, highlighting the potential of microbiome-based interventions to improve outcomes in children facing this critical complication.

microbiology↗

bioRxiv2025

distQTL: Distribution Quantitative Trait Loci Identification by Population-Scale Single-Cell Data

Mapping expression quantitative trait loci (eQTLs) is a powerful method to study how genetic variation influences gene expression. Traditional bulk eQTL methods rely on averaged gene expression across a possibly heterogeneous mixture of cells, which can obscure underlying regulatory heterogeneity. Single-cell eQTL methods circumvent the averaging artifacts, providing an immense opportunity to interrogate transcriptional regulation at a much finer resolution. Recent developments in metric space regression methods allow the use of full empirical distributions as response objects instead of simple summary statistics such as mean. Here, we leverage Frechet regression to identify distribution QTLs (distQTLs) using population-scale single-cell RNA sequencing data. We apply distQTL to the OneK1K cohort, consisting of scRNA-seq data of peripheral blood mononuclear cells from 982 donors, and compare results to various eQTL approaches based on summary statistics and mixed effects modeling. We demonstrate the superior performance of distQTL across different gene expression contexts compared to other methods and benchmark our results against findings from the Genotype-Tissue Expression Project. Finally, we orthogonally validate calls from distQTL using cell-type-specific epigenomic profiles.

genomics↗

bioRxiv2025

XPC loss-of-function triggers melanomagenesis through CDKN2A downregulation

We identified a novel XPC variant, c.2420+5G>A (XPCvar), in siblings with multiple melanomas, inherited alongside c.779+1G>T, which results in an absent or disrupted protein. However, they did not exhibit significantly higher nucleotide excision repair (NER) deficits compared to their unaffected parents, suggesting an NER-independent tumor suppressor function for XPC. XPC knockdown increased cell proliferation and tumorigenicity in vitro without affecting NER. Single-cell RNA sequencing revealed lower Cdkn2a in Xpcvar/var mouse melanocytes. Additionally, XPC knockdown downregulated CDKN2A in vitro. Furthermore, patient fibroblasts showed decreased p16INK4a, which was rescued by XPC overexpression. ChIP-PCR and luciferase assays confirmed XPC binding to the CDKN2A promoter, initiating transcription. Premature stop codon read-through, with gentamicin, restored XPC and p16INK4A in patient fibroblasts. These suggest that XPC regulates CDKN2A and XPC loss might promote melanomagenesis by downregulating CDKN2A, independent of its NER function. We provide preclinical evidence for potential preventive and/or therapeutic strategies for similarly affected individuals. STATEMENT OF SIGNIFICANCECharacterizing a novel XPC variant identified in patients with melanoma revealed a non-canonical role for XPC in regulating CDKN2A transcription. XPC binding to the CDKN2A promoter is crucial for CDKN2A expression and might suppress melanomagenesis. This expands our understanding of melanomagenesis and suggests potential therapies targeting XPC-mediated regulation of CDKN2A.

cancer biology↗

bioRxiv2025

Age-Dependent Patterns of Gut Bifidobacterium Microbiome Diversity across child Cohorts in a Multi-Ethnic population, Western China

High-throughput sequencing has provided unprecedented opportunities to elucidate the role of human gut microbiota. However, current studies have primarily focused on infant and adult cohorts, leaving biomarkers associated with the development of transitional children unclear, particularly in revealing geographic, multi-ethnic group underrepresented. Here, we analyzed fecal samples from 776 infants and children aged 0 to 15 years with amplicon sequencing of the 16S rRNA and groEL gene, representing multi-ethnic groups from different residential locations in the Yining region of Xinjiang. First, we systematically characterized the gut microbiota Spectrum of children in the Ili region. As age increases, the diversity and functional composition of the microbiota become richer and more stable, with Bifidobacterium consistently dominating the community. Utilizing Bayesian regression models, we identified a cluster of microbiota strongly associated with growth and development in children, which phylogenetically corresponds to Bifidobacterium breve. Finally, we included another similar study in the species-level of Bifidobacterium, and metrics of the age-related effect sizes showed heterogeneity across ethnic groups (Uyghur vs Han: {beta}Deming = 4.40 and Kazakh vs Han: {beta}Deming = 4.33). In conclusion, this study provides novel insights into the developmental trajectories of the gut microbiome in children and its relationship with health. IMPORTANCEThe intestinal microbial markers associated with the development of geographically diverse, multi-ethnic children, particularly those represented by Bifidobacterium species, have been elucidated in this study. Through the application of Bayesian regression models, we identified a microbiome profile closely linked to childhood growth and development, specifically phylogenetically aligned with Bifidobacterium breve. When incorporating a comparable study conducted at the species level of another Bifidobacterium, it was observed that age-related effect sizes varied among different ethnic groups, offering novel insights into the developmental trajectory of childrens gut microbiota and its implications for health.

microbiology↗

bioRxiv2025

Metabolic Signatures of Immune Checkpoint Inhibitor Response in Gynecologic Cancers: Insights from Flux Balance Analysis

Modifiers of immune checkpoint inhibitor (ICI) responses in cancer patients are complex and remain poorly characterized, especially in gynecologic cancers. In this study, we explored fluxomic biomarkers that differentiate responders from non-responders to ICIs in a series of 49 patients with gynecologic cancers, including ovarian, cervical, and endometrial cancers. By applying metabolic enzyme expression as constraints, we utilized an objective-customizable flux balance analysis within a genome-scale metabolic model to predict the metabolic flux differences between responders versus non-responders of ICI treatment. We identified three reactions with consistent differential activity across all ten different optimization objectives: Succinate Dehydrogenase (SUCD1m) in the citric acid cycle, NADH: Guanosine-5-Phosphate Oxidoreductase (r0276) involved in purine catabolism, and Ornithine Transaminase Reversible, Mitochondrial (ORNTArm) in the urea cycle. Additionally, reactions within the folate cycle subsystem, particularly involving MTHFD2, demonstrated significance in distinguishing treatment responses, aligning with previous findings linking MTHFD2 to immune evasion and tumor progression. To further analyze the association between metabolic features and survival outcomes, we implemented machine learning models that integrate multi-omics data. Our model included clinical-pathologic, molecular-genomic features (gene expression, TGF-{beta} score, immune cell abundance from transcriptomic deconvolution), and significant reaction fluxes. Our findings suggest that SUCD1m, MTHFDm and ORNTArm are important metabolic biomarkers that could serve as predictive indicators for ICI response and, if validated in a larger cohort, may guide the development of targeted therapies to enhance treatment efficacy for gynecologic cancer patients. This study highlights the use of genome-scale metabolic modeling to identify clinically relevant biomarkers and improve therapeutic strategies.

systems biology↗