Biology subjects

Antman, T.

Publications and source records attributed to Antman, T..

3 recordsLinked to original sources

bioRxiv2025

Learning the DNA syntax of human microbiomes to infer health and disease

The human microbiome is a key factor in human health and alterations in community structure are associated with diverse pathological conditions. However, defining universal criteria to distinguish healthy from altered microbiome configurations remains challenging due to inter- and intra-individual variability, database-dependent approaches, and the complexity of analyzing numerous microbial features simultaneously. Here, we developed an approach that learns the syntax of the entire DNA of human microbial communities, using Sequence-Informed GC-normalized 4-mers (SIG-mers) that feed into statistical and machine learning frameworks. We identified distinct SIG-mer signatures that differentiate microbiomes of body sites across diverse healthy human populations. These signatures reveal both global microbiome shifts and individual-specific dynamics in response to antibiotic treatments and in chronic inflammatory disease. Leveraging machine learning models, we inferred health- and disease-associated microbiome states from SIG-mer profiles, capturing the degree of perturbation and disease severity. Our findings highlight SIG-mer profiling as a robust, unbiased and broadly applicable approach for personalized microbiome diagnostics and guiding therapeutic interventions.

microbiology↗

bioRxiv2025

Global DNA signatures of temperature and nutrient limitation in prokaryotes

Microorganisms adapt to their environment through changes in both their genes and overall genome composition. However, identifying universal principles of genomic adaptation remains challenging because different environments present multiple, overlapping selective pressures. To overcome this challenge, we analyzed DNA composition patterns across diverse environments using machine learning. By examining tetranucleotide frequencies from 1,112 marine and soil metagenomic samples, we discovered that environmental temperature can be accurately predicted from DNA composition alone (R2=0.82). This temperature signal remained robust even when analyzing individual bacterial phyla and classes, suggesting a fundamental adaptive response. To examine this adaptation mechanism, we analyzed GC content relationships with temperature and found opposing relationships in different environments: positive correlations in soil but negative correlations in marine samples. We show that this inverse relationship in marine environments is driven by nutrient availability, as GC content increases with nutrient levels while nutrients decrease with temperature in marine ecosystems. Despite these contrasting GC patterns, we identified specific tetranucleotides composed of equal numbers of GC and AT bases (50% GC content) that showed consistent temperature correlations across all environments. These findings reveal a complex interplay between temperature adaptation and nutrient limitation in shaping microbial genomes.

microbiology↗

bioRxiv2021

A cell-free assay for rapid screening of inhibitors of hACE2-receptor - SARS-CoV-2-Spike binding

We present a cell-free assay for rapid screening of candidate inhibitors of protein binding, focusing on inhibition of the interaction between the SARS-CoV-2 Spike receptor binding domain (RBD) and human angiotensin-converting enzyme 2 (hACE2). The assay has two components: fluorescent polystyrene particles covalently coated with RBD, termed virion-particles (v-particles), and fluorescently-labeled hACE2 (hACE2F) that binds the v-particles. When incubated with an inhibitor, v-particle - hACE2F binding is diminished, resulting in a reduction in the fluorescent signal of bound hACE2F relative to the non-inhibitor control, which can be measured via flow cytometry or fluorescence microscopy. We determine the amount of RBD needed for v-particle preparation, v-particle incubation time with hACE2F, hACE2F detection limit, and specificity of v-particle binding to hACE2F. We measure the dose response of the v-particles to a known inhibitor. Finally, we demonstrate that RNA-hACE2F granules trap v-particles effectively, providing a basis for potential RNA-hACE2F therapeutics.

synthetic biology↗