Biology subjects

Langa, J.

Publications and source records attributed to Langa, J..

3 recordsLinked to original sources

bioRxiv2025

Integrative holo-omic data analysis predicts interactions across the host-microbiome axis

Understanding the interplay between host organisms and their microbiomes is central to the development of sustainable food systems. However, high dimensionality and spurious associations remain major obstacles to extracting meaningful biological insight from multi-omic host-associated microbiome data; a challenge further exacerbated when "holo-omic" analyses across the host-microbiome boundary is considered. Here, we show that a computational method designed for multi-omic analysis in eukaryotes can be leveraged to integrate and analyse five layers of holo-omic data from porcine hosts and their gut microbiomes. We collected caecal tissue and digesta samples during a feeding trial that tested the impact of microbiota-directed fibres (acetylated galactoglucomannan) at critical developmental stages. From 800,000 features including microbial and host genes, metagenome-assembled genomes, and metabolites from caecal tissue and digesta, we used multiset correlation and factor analysis to select the most relevant features for capturing coordinated patterns across omic layers. From these features, we predicted over 2,000 putative host-microbiome interactions based on co-occurrence. Some of them reflected previously known relationships between animal and microbiome features, such as microbial genes for carbohydrate metabolism being linked to glycoside abundances in host tissue. Other predicted co-occurrences included features that were not detected in single-omic analysis and offer new hypotheses of host-microbiome interactions that warrant future investigation. Hence, we showcase an application of holo-omic analysis that avoids common pitfalls in high-dimensional data analysis; identifies known interactions as a form of validation; and most importantly, predicts new leads for understanding host-microbiome symbiosis. ImportanceWhile study systems involving mammalian hosts and their microbiomes are inherently complex, multi- and holo-omic analyses promise to provide interpretable results with translational value for the animal production industry. Unfortunately, computational methods capable of this kind of integration are currently scarce, as most existing multi-omics approaches have been developed for analysis of data layers within a single multicellular organism. We propose to adapt existing multi-omic methods for holo-omics by combining feature selection and interaction inference. This two-step analysis approach addresses common challenges in data-driven studies and can be implemented with a variety of tools for feature selection and interaction modelling. Through this holistic approach, we show that both known and novel relationships across the holobiont axis can be identified in a data-driven manner, offering new targets for the continued study of host-microbiome interactions and the effect of dietary interventions on production animals.

bioinformatics↗

bioRxiv2025

Micro-scale spatial metagenomics: revealing high-resolution spatial biogeography of gut microbiomes

Spatial organisation is a fundamental yet poorly resolved aspect of gut microbial ecology. Conventional shotgun metagenomics provides rich functional information but relies on homogenised, macro-scale samples that obscure the micron-scale distributions critical for understanding microbial community dynamics. Here, we introduce Micro-Scale Spatial Metagenomics (MSSM), a new methodological framework that couples laser micro-dissection of tissue sections, ultra-low-input library preparation, and genome-resolved bioinformatics to reconstruct microbial communities from intestinal microsamples measuring as little as [~]500 {micro}m{superscript 2} ({approx}100 bacterial cells). We describe a fully optimised laboratory and computational pipeline that enables quantitative, strain-resolved, and functionally informed spatial profiling directly from intact gut tissue. Using chicken intestinal samples, we validated MSSM through combinatorial single-cell fluorescence in situ hybridisation (FISH) imaging and comparisons with macro-scale metagenomics, demonstrating its robustness and accuracy. MSSM captured fine-scale heterogeneity in taxonomic and functional composition across intestinal cryosections, hinting at spatially structured assemblages and segregation of metabolic capacities. Strain-level analyses uncovered coexisting Lawsonibacter lineages exhibiting distinct spatial distributions and host-specific occurrence patterns, while SNP-level microdiversity analyses showed that genetically coherent clonal populations cluster at spatial scales below [~]200 {micro}m. By enabling shotgun metagenomics at micron resolution, MSSM closes a longstanding methodological gap and provides a scalable platform for studying microbial ecosystems in situ. This approach unlocks a previously inaccessible view of microbial biogeography, offering new opportunities to investigate host-microbe and microbe-microbe interactions, and the spatial principles governing gut ecosystems. Significance statementUnderstanding how microbial communities are organised in space is essential to explaining their ecological and functional roles, yet microbiome research still relies overwhelmingly on bulk, spatially averaged measurements. We introduce micro-scale spatial metagenomics (MSSM), the first method that brings shotgun metagenomics to the microscale, enabling direct measurement of functional and taxonomic variation across regions containing as few as [~]100 cells. Unlike existing spatial approaches, MSSM reconstructs complete genomes and resolves strain-level diversity within intact tissue, allowing researchers to map metabolic potential, microdiversity, and community structure in situ. By coupling high-resolution sequencing with spatial context, MSSM reveals a previously inaccessible layer of microbial organisation, transforming how host-associated ecosystems can be studied.

microbiology↗

bioRxiv2018

Transient fibrosis resolves via fibroblast inactivation in the regenerating zebrafish heart

In the zebrafish (Danio rerio), regeneration and fibrosis after cardiac injury are not mutually exclusive responses. Upon cardiac cryoinjury, collagen and other extracellular matrix (ECM) proteins accumulate at the injury site. However, in contrast to the situation in mammals, fibrosis is transient in zebrafish and its regression is concomitant with regrowth of the myocardial wall. Little is known about the cells producing this fibrotic tissue or how it resolves. Using novel genetic tools to mark periostin b- and collagen 1alpha2 (col1a2)-expressing cells in combination with transcriptome analysis, we explored the sources of activated fibroblasts and traced their fate. We describe that during fibrosis regression, fibroblasts are not fully eliminated, but become inactivated. Unexpectedly, limiting the fibrotic response by genetic ablation of col1a2-expressing cells impaired cardiomyocyte proliferation. We conclude that ECM-producing cells are key players in the regenerative process and suggest that anti-fibrotic therapies might be less efficient than strategies targeting fibroblast inactivation.\n\nSCIENTIFIC STATEMENTAfter myocardial infarction in the mammalian heart, millions of cardiomyocytes are lost and replaced by fibrotic scar tissue. While fibrosis is persistent in adult mammals, there are some vertebrates, including zebrafish, with the capacity for regeneration. This process does not occur in the absence of fibrosis. Here we studied subpopulations of collagen producing cells and analyzed their fate after complete regeneration of the zebrafish myocardium. Our data show that fibroblasts persisted in the regenerated heart, but shut down the profibrotic program. While fibrosis could be considered as detrimental to the regeneration process, our study reveals a positive effect on cardiomyocyte proliferation. Accordingly, a fibrotic response can be beneficial for heart regeneration.

developmental biology↗