Biology subjects

Konstantinovsky, T.

Publications and source records attributed to Konstantinovsky, T..

5 recordsLinked to original sources

bioRxiv2026

A computable probability landscape for T cell receptor repertoire sampling and comparison

Finite sampling complicates interpretation and comparison of T cell receptor (TCR) repertoires. We introduce BEAM, a probability model for TCR{beta} complementarity-determining region 3 amino-acid sequences that combines local sequence dependence with exact normalisation. Its tractable local structure permits deterministic evaluation of sequence-pattern probabilities and sampling expectations without enumerating or Monte Carlo sampling the sequence domain. A reference built from 38,538 human repertoires links sampling depth to expected sequence recovery, recurrence, overlap and publicness, the number of cohort repertoires containing a sequence. Models built from individual repertoires define distances attributable to sequence lengths and local patterns. BEAM improves held-out sequence prediction over controls matched for length and individual-position frequencies, ranks sequence publicness in an external cohort and matches CD4 and CD8 repertoires across independent studies. BEAM therefore provides a tractable observational probability landscape for depth-aware sampling calculations and interpretable repertoire comparison.

bioinformatics↗

bioRxiv2024

An unbiased comparison of immunoglobulin sequence aligners

Adaptive Immune Receptor Repertoire sequencing (AIRR-seq) is critical for our under-standing of the adaptive immune systems dynamics in health and disease. Reliable analysis of AIRR-seq data depends on accurate Immunoglobulin (Ig) sequence alignment. Various Ig sequence aligners exist, but there is no unified benchmarking standard representing the complexities of AIRR-seq data, obscuring objective comparisons of aligners across tasks. Here, we introduce GenAIRR, an efficient simulation framework for generating Ig sequences alongside their ground truths. GenAIRR realistically simulates the intricacies of V(D)J recombination, somatic hypermutation, and an array of sequence corruptions. We comprehensively assessed prominent Ig sequence aligners across various metrics, unveiling unique performance characteristics for each aligner. The GenAIRR-produced datasets, combined with the proposed rigorous evaluation criteria, establish a solid basis for unbiased benchmarking of immunogenetics computational tools. It sets up the ground for further improving the crucial task of Ig sequence alignment, ultimately enhancing our understanding of adaptive immunity.

bioinformatics↗

bioRxiv2023

A Novel Approach to T-Cell Receptor Beta Chain (TCRB) Repertoire Encoding Using Lossless String Compression

T-cell diversity is crucial for producing effective receptors that can recognize the pathogens encountered throughout life. A stochastic biological process known as VDJ recombination accounts for the high diversity of these receptors, making their analysis challenging. We present a new approach to sequence encoding and analysis, based on the Lempel-Ziv 76 algorithm (LZ-76). By creating a graph-like model, we identify specific sequence features and produce a new encoding approach to an individuals repertoire. We demonstrate that this repertoire representation allows for various applications, such as generation probability inference, informative feature vector derivation, sequence generation, and a new measure for diversity estimation.

immunology↗

bioRxiv2022

Epigenetic aging waves:Artificial intelligence detects clustering of switch points in DNA methylation rate in defined sex-dependent age periods

BackgroundAging is linked to hypermethylation of CpG sites on promoters and enhancers, along with loss of methylation in intergenic zones. That such changes are not necessarily a continuous process is exemplified by the extensive changes in DNA methylation during development with another significant time of change during adolescence. However, the relation between age and DNA methylation during adult life has not been systematically evaluated. In particular, potential changes in methylation trends in the same CpGs over the years that may occur with aging remain largely unexplored. MethodsHere we set out to determine the average trends by age of the CpG sites represented in the Illumina 450 platform, based on data from 2143 subjects of the age range of 20 to 80 years, compiled from 24 different cohorts. Using several mathematical procedures, we initially separated stationary probes from probes whose methylation changes with age. Among the latter, representing [~]20% of the probes, we then focused on the identification of CpG sites with switch points, i.e., a point where a stable trend of change in the age-averaged methylation is replaced by another linear trend. ResultsUsing several mathematical modeling steps, we generated a machine learning model that identified 5175 CpG sites with switch points in age-related changes in the trend of methylation over the years. Switch points reflect acceleration, deceleration or change of direction of the alteration of methylation with age. The 5175 switch points were limited to 2813 genes in three waves, 80% of which were identical in men and women. A medium-size wave was seen in the early forties, succeeded by a dominant wave as of the late fifties, lasting up to 8 years each. Waves appeared[~]4-5 years earlier in men. No switch points were detected on CpGs mapped to the X chromosome. ConclusionIn non-stationary CpG sites, concomitant switch points in age related changes in methylations can be seen in a defined group of sites and genes, which cluster in 3 age- and sex-specific waves.

genomics↗

bioRxiv2021

Deconvolution of the epigenetic age discloses distinct inter-personal variability in epigenetic aging patterns

BackgroundThe epigenetic age can now be extrapolated from one of several epigenetic clocks, which are based on age-related changes in DNA methylation levels at specific multiple CpG sites. Accelerated aging, calculated from the discrepancy between the chronological age and the epigenetic age, has shown to predict morbidity and mortality rate. We assumed that deconvolution of epigenetic age to its components could shed light on the diversity of epigenetic, and by inference, on inter-individual variability in the causes of biological aging. ResultsUsing the Horvath original epigenetic clock, we identified several CpG sites linked to distinct genes that quantitatively explain much of the interpersonal variability in epigenetic aging, with CpG sites related to secretagogin and malin being the most variable. We show that equal epigenetic age in different subjects can result from variable contribution size of the same CpG sites to the total epigenetic age. In a healthy cohort, the most variable CpG sites are responsible for accelerated and decelerated epigenetic aging, relative to chronological age. ConclusionsOf the 353 CpG sites that form the basis for the Horvath epigenetic age, we have found the CpG sites that are responsible for accelerated and decelerated epigenetic aging in healthy subjects. However, the relative contribution of each site to aging varies between individuals, leading to variable personal aging patterns. Our findings pave the way to form personalized aging cards allowing the identification of specific genes related to CpG sites, as aging markers, and perhaps treatment of these targets in order to hinder undesirable age drifting.

developmental biology↗