Publications by authors named "Liron Zahavi"

Aging varies significantly among individuals of the same chronological age, indicating that biological age (BA), estimated from molecular and physiological biomarkers, may better reflect aging. Prior research has often ignored sex-specific differences in aging patterns and mainly focused on aging biomarkers from a single data modality. Here we analyze a deeply phenotyped longitudinal cohort (10K project, Israel) of 10,000 healthy individuals aged 40-70 years that includes clinical, physiological, behavioral, environmental and multiomic parameters.

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Genome-wide association studies (GWASs) have provided numerous associations between human single-nucleotide polymorphisms (SNPs) and health traits. Likewise, metagenome-wide association studies (MWASs) between bacterial SNPs and human traits can suggest mechanistic links, but very few such studies have been done thus far. In this study, we devised an MWAS framework to detect SNPs and associate them with host phenotypes systematically.

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A CRISPR-based tool reveals intestinal microbiota gene expression through time.

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Multiple sclerosis (MS) is an immune-mediated disease whose precise etiology is unknown. Several studies found alterations in the microbiome of individuals with MS, but the mechanism by which it may affect MS is poorly understood. Here we analyze the microbiome of 129 individuals with MS and find that they harbor distinct microbial patterns compared with controls.

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Cellular function is critically regulated through degradation of substrates by the proteasome. To enable direct analysis of naturally cleaved proteasomal peptides under physiological conditions, we developed mass spectrometry analysis of proteolytic peptides (MAPP), a method for proteasomal footprinting that allows for capture, isolation and analysis of proteasome-cleaved peptides. Application of MAPP to cancer cell lines as well as primary immune cells revealed dynamic modulation of the cellular degradome in response to various stimuli, such as proinflammatory signals.

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Gene expression burdens cells by consuming resources and energy. While numerous studies have investigated regulation of expression level, little is known about gene design elements that govern expression costs. Here, we ask how cells minimize production costs while maintaining a given protein expression level and whether there are gene architectures that optimize this process.

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