Biology subjects

Berland, M.

Publications and source records attributed to Berland, M..

8 recordsLinked to original sources

bioRxiv2026

Hydrogen metabolism shapes gut microbiome into health-associated configurations

The human gut microbiome exhibits reproducible configurations, yet the ecological forces connecting them to health remain unclear. Here, using enterosignature-based stratification of 5,170 individuals from the Le French Gut cohort, we identified hydrogen disposal as a key determinant of population-scale microbiome configurations, independently replicated in a meta-cohort (n = 5,107). Microbial configurations followed a continuum of hydrogen recycling capacity and redox-associated functions, aligned with dietary patterns and health indicators. Methanogenesis-dominant partitions were associated with more favorable health profiles, whereas acetogenesis-enriched partitions exhibited features of low-grade inflammation, and increased digestive symptoms, perceived stress and antidepressant use. Experimental characterization of mucin profiles highlighted differences across partitions and alterations in Bacteroides-enriched configurations. Together, our findings support an ecological host-microbiome framework linking hydrogen metabolism, redox ecology, and host health, offering microbiome-informed targets for precision intervention. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=128 SRC="FIGDIR/small/722951v1_ufig1.gif" ALT="Figure 1"> View larger version (29K): org.highwire.dtl.DTLVardef@e7b8d1org.highwire.dtl.DTLVardef@116ab09org.highwire.dtl.DTLVardef@136f1f8org.highwire.dtl.DTLVardef@480097_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2025

NeighborFinder: an R package inferring local microbial network around a species of interest

1MotivationUnderstanding interactions from microbiome data is a central aspect in microbial ecology, as it provides insights into ecosystem stability, disease mechanisms, and can be used to design synthetic communities. Current network inference tools reconstruct global networks from co-abundance data, which means they capture the overall correlation structure for the entire set of taxa considered. These approaches are computationally intensive and suboptimal when the focus is on the local neighborhood of specific taxa of interest. ResultsWe introduce NeighborFinder, a local network inference method that enables the targeted discovery of direct neighbors around a species of interest. Using cross-validated multiple linear regression with[l] 1 penalty and microbiome-specific filters, our approach infers interpretable species-centered interactions, with F1 score [≥] 0.95 on simulated cohorts ranging from 250 to 1000 samples. This method is well-suited for large metagenomic datasets and is particularly valuable for exploratory studies where the targeted hypotheses outweigh the need for global community structure. The approach complements existing methods by being a biologically intuitive and computationally efficient. Availability and ImplementationThe R package is freely available on GitHub: https://github.com/metagenopolis/NeighborFinder. The data and source code used to calculate performances and produce the use case example in this paper can be found respectively at: https://doi.org/10.57745/UPITJ0 and https://doi.org/10.57745/HJLWW4. Supplementary informationSupplementary data are available

systems biology↗

bioRxiv2023

Aggregating network inferences: towards useful networks

Modeling microbial interactions as sparse and reproducible networks is a major challenge in microbial ecology. Direct interactions between the microbial species of a biome can help to understand the mechanisms through which microbial communities influence the system. Most state-of-the art methods reconstruct networks from abundance data using Gaussian Graphical Models, for which several statistically grounded and computationnally efficient inference approaches are available. However, the multiplicity of existing methods, when applied to the same dataset, generates very different networks. In this article, we present OneNet, a consensus network inference method that combines seven methods based on stability selection. This resampling procedure is used to tune a regularization parameter by computing how often edges are selected in the networks. We modified the stability selection framework to use edge selection frequencies directly and combine them in the inferred network to ensure that only reproducible edges are included in the consensus. We demonstrated on synthetic data that our method generally led to slightly sparser networks while achieving much higher precision than any single method. We further applied the method to gut microbiome data from liver-cirrothic patients and demonstrated that the resulting network exhibited a microbial guild that was meaningful in terms of human health.

bioinformatics↗

bioRxiv2021

A combined test for feature selection on sparse metaproteomics data - alternative to missing value imputation

One of the difficulties encountered in the statistical analysis of metaproteomics data is the high proportion of missing values, which are usually treated by imputation. Nevertheless, imputation methods are based on restrictive assumptions regarding missingness mechanisms, namely "at random" or "not at random". To circumvent these limitations in the context of feature selection in a multi-class comparison, we propose a univariate selection method that combines a test of association between missingness and classes, and a test for difference of observed intensities between classes. This approach implicitly handles both missingness mechanisms. We performed a quantitative and qualitative comparison of our procedure with imputation-based feature selection methods on two experimental data sets, as well as simulated data with various scenarios regarding the missingness mechanisms and the nature of the difference of expression (differential intensity or differential missingness). Whereas we observed similar performances in terms of prediction on the experimental data set, the feature ranking and selection from various imputation-based methods were strongly divergent. We showed that the combined test reaches a compromise by correlating reasonably with other methods, and remains efficient in all simulated scenarios unlike imputation-based feature selection methods.

bioinformatics↗

bioRxiv2021

StrainFLAIR: Strain-level profiling of metagenomic samples using variation graphs

Current studies are shifting from the use of single linear references to representation of multiple genomes organised in pangenome graphs or variation graphs. Meanwhile, in metagenomic samples, resolving strain-level abundances is a major step in microbiome studies, as associations between strain variants and phenotype are of great interest for diagnostic and therapeutic purposes. We developed StrainFLAIR with the aim of showing the feasibility of using variation graphs for indexing highly similar genomic sequences up to the strain level, and for characterizing a set of unknown sequenced genomes by querying this graph. On simulated data composed of mixtures of strains from the same bacterial species Escherichia coli, results show that StrainFLAIR was able to distinguish and estimate the abundances of close strains, as well as to highlight the presence of a new strain close to a referenced one and to estimate its abundance. On a real dataset composed of a mix of several bacterial species and several strains for the same species, results show that in a more complex configuration StrainFLAIR correctly estimates the abundance of each strain. Hence, results demonstrated how graph representation of multiple close genomes can be used as a reference to characterize a sample at the strain level. Availabilityhttp://github.com/kevsilva/StrainFLAIR

bioinformatics↗

bioRxiv2019

Unique Features of Sub-Cortical Circuits in A Macaque Model of Congenital Blindness

There is extensive modification of the functional organization of the brain in the congenital blind human, although there is little understanding of the structural underpinnings of these changes. The visual system of macaque has been extensively characterized both anatomically and functionally. We have taken advantage of this to examine the influence of the congenital blindness in macaque resulting from the removal of the retina during in utero development. Developmental anophthalmia in macaque effectively removes the normal influence of the thalamus on cortical development leading to an induced hybrid cortex (HC) combining features of primary visual and extrastriate cortex. Here we show that retrograde tracers injected in early visual areas including hybrid cortex reveals a drastic reduction of cortical projections of the reduced lateral geniculate nucleus. In addition, there is an important expansion of projections from the pulvinar complex to the hybrid cortex, compared to the controls. These findings show that the functional consequences of congenital blindness need to be considered in terms of both modifications of the inter-areal cortical network and the ascending visual pathways.

neuroscience↗

bioRxiv2019

Refinement of the primate corticospinal pathway during prenatal development

Perturbation of the developmental refinement of the corticospinal pathway leads to motor disorders. In non-primates developmental refinement is well documented, however in primates invasive investigations of the developing corticospinal pathway have been confined to neonatal and postnatal stages when refinement is relatively modest.\n\nHere, we investigated the developmental changes in the distribution of corticospinal projection neurons in cynomolgus monkey. Injections of retrograde tracer at the cervical levels of the spinal cord at embryonic day (E) 95 and E105 show that (i) areal distribution of back-labeled neurons is more extensive than in the neonate and dense labeling is found in prefrontal, limbic, temporal and occipital cortex; (ii) distributions of contra- and ipsilateral projecting corticospinal neurons are comparable in terms of location and numbers of labeled neurons, in contrast to the adult where the contralateral projection is an order of magnitude higher than the ipsilateral projection. Findings from one largely restricted injection suggest a hitherto unsuspected early innervation of the gray matter.\n\nIn the fetus there was in addition dense labeling in the central nucleus of the amygdala, the hypothalamus, the subthalamic nucleus and the adjacent region of the zona incerta, subcortical structures with only minor projections in the adult control.

neuroscience↗

bioRxiv2017

Cortical Connectivity In A Macaque Model Of Congenital Blindness

AbstractBrain-mapping of the congenitally blind human reveals extensive plasticity(1). The visual cortex of the blind has been observed to support higher cognitive functions including language and numerical processing(2, 3). This functional shift is hypothesized to reflect a metamodal cortical function, where computations are defined by the local network. In the case of developmental deafferentation, local circuits are considered to implement higher cognitive functions by accommodating diverse long-distance inputs(4-7). However, the extent to which visual deprivation triggers a reorganization of the large-scale network in the cortex is still controversial(8). Here we show that early prenatal ablation of the retina, an experimental model of anophthalmia in macaque, leads to a major reduction of area V1 and the creation of a default extrastriate cortex (DEC)(9, 10). Anophthalmic and normal macaques received retrograde tracer injections in DEC, as well as areas V2 and V4 post-natally. This revealed a six-fold expansion of the spatial extent of local connectivity in the DEC and a surprisingly high location of the DEC derived from a computational model of the cortical hierarchy(11). In the anophthalmic the set of areas projecting to the DEC, area V2 and V4 does not differ from that of normal adult controls, but there is a highly significant increase in the relative cumulative weight of the ventral stream areas input to the early visual areas. These findings show that although occupying the territory that would have become primary visual cortex the DEC exhibits features of a higher order area, thus reflecting a combination of intrinsic and extrinsic factors on cortical specification. Understanding the interaction of these contributing factors will shed light on cortical plasticity during primate development and the neurobiology of blindness.

neuroscience↗