Biology subjects

Im, C.

Publications and source records attributed to Im, C..

8 recordsLinked to original sources

bioRxiv2026

BenchRep-T: A Systematic Evaluation of T-Cell Repertoire-Based Disease Diagnostics

Adaptive immune receptor repertoire sequencing data has emerged as a promising potential modality for disease diagnosis, relying on computational methods to analyze T-cell receptor (TCR) sequences from an individuals blood sample. Published methods rely on different cohorts, data preprocessing pipelines, and evaluation metrics, making direct comparison across methods challenging. We present BenchRep-T, a unified benchmark that standardizes multiple publicly available TCR repertoire datasets and evaluates nine computational approaches, spanning statistical enrichment of shared sequences, feature-engineered ensembles, deep learning, and sequence clustering. BenchRep-T evaluates methods on four tasks: disease classification across conditions, performance scaling under restricted sequence-sampling depth, recovery of known antigen-specific driver sequences, and evaluation of sensitivity to demographic confounding. Under controlled evaluation, simple baselines prove competitive, with tree-based models trained on V- and J-gene usage and short sequence motifs approaching the classification performance of more complex methods. Our findings underscore the complexity of modeling TCR repertoire data, and show that no single method dominates across all tasks. BenchRep-T provides a framework for rigorous and reproducible evaluation of TCR repertoire classification methods to accelerate the development of immune repertoire-based diagnostics.

immunology↗

bioRxiv2025

Different growth pattern during microbial electrosynthesis using C. ljungdahlii evolutionary adapted on iron

Clostridium ljungdahlii is an acetogen used for syngas fermentation and capable of microbial electrosynthesis. While C. ljungdahlii has potential for industrial application because of its broad spectrum of metabolites and substrates, including CO2 and CO, the efficiency of extracellular electron uptake in a bioelectrochemical system is low. Therefore, C. ljungdahlii was evolutionary adapted on iron as sole electron source with the aim to improve extracellular electron uptake. Over 38 batches, 95% of the culture was replaced with fresh medium biweekly to retain iron-attached C. ljungdahlii, leading to improved acetate production rates with each cycle. Eight isolated strains were tested on fructose, H2 and CO2, and iron to screen evolved mutants with desired mutations. Compared to the wild-type, growth on fructose was similar and growth on H2 and CO2 was, surprisingly, worse, with only minor differences between isolates. The isolated mutants produced acetate at a rate of 0.14 {+/-} 0.01 mM/d on iron, while the wild-type strain produced 0.75 {+/-} 0.14 mM/d. Whole genome sequencing of isolated mutants revealed 16 mutations, of which seven mutations were found in all isolates. Mostly, membrane proteins were mutated. In a BES reactor, acetate production ceased after day 1. The optical density (OD) of isolate #8 stopped increasing after day 2, reaching 0.122 {+/-} 0.005, followed by the production of formate and ethanol. The wild-type strain continued to grow until day 4, reaching an OD of 0.177 {+/-} 0.003. These results may indicate that C. ljungdahlii slows down growth and produces ethanol as an energy reserve as an evolutionary strategy for survival in an electron-limited environment.

microbiology↗

bioRxiv2025

Heterologous expression of pyruvate formate lyase enhances cell growth of Clostridium ljungdahlii during microbial electrosynthesis

Slow cell growth and low biomass yields are hurdles for gas fermentation by acetogens. Microbial electrosynthesis (MES) utilizes acetogens as biocatalysts to reduce CO2 and produce commodity chemicals using electricity. However, limited electron supply in a bioelectrochemical system (BES) aggravates the poor cell growth of acetogens resulting in low productivities. Formate is a soluble C1 feedstock that can be produced by CO2 reduction (1). Thus, assimilation of formate can unburden the amount of electrons required for MES. Acetobacterium woodii posseses multiple pyruvate formate lyase (PFL) genes that are upregulated during formatotrophic growth. In this study, Clostridium ljugdahlii was engineered to heterologously express a pfl geneset of A. woodii to increase the cell growth of C. ljungdahlii during microbial electrosynthesis. Different combinations of pfl A and pfl B from A. woodii were tested in C. ljungdahlii to find the best working combination under control of Pfdx-riboswitch expression system. Expression of pfl B1 and pflA of A. woodii showed higher maximum OD of C. ljugdahlii under H2:CO2 condition with supplementation of 80 mM sodium formate. More than 40 mM of sodium formate caused significantly longer lag phase but the lag phase could be shortened after adaptation in 80 mM of sodium formate. At the end, the engineered strain showed improved cell growth (ODmax 0.22 {+/-} 0.05) and acetate production (21.8 {+/-} 5.6 mM) during microbial electrosynthesis compared to the control strain (ODmax 0.10 {+/-}0.06 and 10.2 {+/-}2.5 mM acetate). These results will be useful for strain development for microbial electrosynthesis, as well as gas fermentation. HighlightsO_LIDifferent combinations of pyruvate formate lyases (pfl Bs) and pyruvate formate lyase acting enzymes (pfl As) from Acetobacterium woodii were tested to improve the cell growth of Clostridium ljungdahlii during gas fermentation and microbial electrosynthesis C_LIO_LIHeterologous expression of pfl B1 and pfl A using riboswitch expression system improved cell growth of C. ljungdahlii under H2:CO2 condition, even without inducer and formate supplementation. C_LIO_LIHigh concentraton of sodium formate caused longer lag phase, which was shortened by adaptation when pfl from A. woodii was heterologously expressed. C_LIO_LICell growth and acetate production of the engineered C. ljungdahlii strain improved during microbial electrosynthesis C_LI

microbiology↗

bioRxiv2024

Sequence-based TCR-Peptide Representations Using Cross-Epitope Contrastive Fine-tuning of Protein Language Models

Understanding T-Cell receptor (TCR) and epitope interactions is critical for advancing our knowledge of the human immune system. Traditional approaches that use sequence similarity or structure data often struggle to scale and generalize across diverse TCR/epitope interactions. To address these limitations, we introduce ImmuneCLIP, a contrastive fine-tuning method that leverages pre-trained protein language models to align TCR and epitope embeddings in a shared latent space. ImmuneCLIP is evaluated on epitope ranking and binding prediction tasks, where it consistently outperforms sequence-similarity based methods and existing deep learning models. Furthermore, ImmuneCLIP shows strong generalization capabilities even with limited training data, highlighting its potential for studying diverse immune interactions and uncovering patterns that improve our understanding of human immune recognition systems.

immunology↗

bioRxiv2023

Learning the Language of Antibody Hypervariability

Protein language models (PLMs) based on machine learning have demon-strated impressive success in predicting protein structure and function. However, general-purpose ("foundational") PLMs have limited performance in predicting antibodies due to the latters hypervariable regions, which do not conform to the evolutionary conservation principles that such models rely on. In this study, we propose a new transfer learning framework called AbMAP, which fine-tunes foundational models for antibody-sequence inputs by supervising on antibody structure and binding specificity examples. Our feature representations accurately predict an antibodys 3D structure, mutational effects on antigen binding, and paratope identification. AbMAPs scalability paves the way for large-scale analyses of human antibody repertoires. AbMAP representations of immune repertoires reveal a remarkable overlap across individuals, overcoming the limitations of sequence analyses. Our findings provide compelling evidence for the hypothesis that antibody repertoires of individuals tend to converge towards comparable structural and functional coverage. We validate AbMAP for antibody optimization, applying it to optimize a set of antibodies that bind to a SARS-CoV-2 peptide and obtaining 82% hit-rate and upto 22-fold increase in binding affinity. We anticipate AbMAP will accelerate the efficient design and modeling of antibodies and expedite the discovery of antibody-based therapeutics. Availability:https://github.com/rs239/ablm

bioinformatics↗

bioRxiv2021

Key Factors in the Cortical Response to Transcranial Electrical Stimulations--A Multi-Scale Modeling Study

Transcranial electrode stimulation (tES), one of the techniques used to apply non-invasive brain stimulation (NIBS), modulates cortical activities by delivering weak electric currents through scalp-attached electrodes. This emerging technique has gained increasing attention recently; however, the results of tES vary greatly depending upon subjects and the stimulation paradigm, and its cellular mechanism remains uncertain. In particular, there is a controversy over the factors that determine the cortical response to tES. Some studies have reported that the electric fields (EF) orientation is the determining factor, while others have demonstrated that the EF magnitude itself is the crucial factor. In this work, we conducted an in-depth investigation of cortical activity in two types of electrode montages used widely--the conventional (C)-tES and high-definition (HD)-tES--as well as two stimulation waveforms--direct current (DC) and alternating current (AC). To do so, we constructed a multi-scale model by coupling an anatomically realistic human head model and morphologically realistic multi-compartmental models of three types of cortical neurons (layer 2/3 pyramidal neuron, layer 4 basket cell, layer 5 pyramidal neuron). Then, we quantified the neuronal response to the C-/HD-tDCS/tACS and explored the relation between the electric field (EF) and the radial fields (RF: radial component of EF) magnitude and the cortical neurons threshold. The EF tES induced depended upon the electrode montage, and the neuronal responses were correlated with the EF rather than the RFs magnitude. The electrode montages and stimulation waveforms caused a small difference in threshold, but the higher correlation between the EFs magnitude and the threshold was consistent. Further, we observed that the neurons morphological features affected the degree of the correlation highly. Thus, the EF magnitude was a key factor in the responses of neurons with arborized axons. Our results demonstrate that the crucial factor in neuronal excitability depends upon the neuron models morphological and biophysical properties. Hence, to predict the cellular targets of NIBS precisely, it is necessary to adopt more advanced neuron models that mimic realistic morphological and biophysical features of actual human cells.

neuroscience↗

bioRxiv2020

Generalizability of "GWAS hits" in clinical populations: Lessons from childhood cancer survivors

With mounting interest in translating GWAS hits from large meta-analyses (meta-GWAS) in diverse clinical settings, evaluating their generalizability in target populations is crucial. Here we consider long-term survivors of childhood cancers from the St. Jude Lifetime Cohort Study and show the limited generalizability of 1,376 robust SNP associations reported in the general population across 12 complex anthropometric and cardiometabolic phenotypes (N=2,231; observed-to-expected replication ratio=0.68, P=2.4x10-9). An examination of five comparable phenotypes in a second independent cohort of survivors from the Childhood Cancer Survivor Study corroborated the overall limited generalizability of meta-GWAS hits to survivors (N=4,212, observed-to-expected replication ratio=0.53, P=1.1x10-16). Meta-GWAS hits were less likely to be replicated in survivors exposed to cancer therapies associated with phenotype risk. Examination of complementary DNA methylation data in a subset of survivors revealed that treatment-related methylation patterns at genomic sites linked to meta-GWAS hits may disrupt established genetic signals in survivors.

genetics↗

bioRxiv2019

Quantifying E2F1 protein dynamics in single cells

The Rb/E2F pathway plays a central role in regulating cell-fate decisions and cell-cycle progression. The E2F1 protein, a major effector of the pathway, is regulated via a combination of transcriptional, translational and posttranslational constraints. Elucidating the regulation and impact of the Rb/E2F pathway requires direct measurement of E2F1 dynamics in single cells. To this end, we have engineered fluorescent E2F1 protein reporters to enable live detection and quantification in single cells. The reporter constructs expressed an E2F1-Venus fusion protein under the regulation of the mouse or human E2F1 promoter and contained or excluded the 3UTR of the E2F1 gene, a sequence that contains miRNA regulatory regions that modulate expression of the protein. Expression of the reporter protein was highly dynamic during the cell cycle: there was no or little fluorescent signal in G0, but levels steadily increased during late G1 and peaked during mid to late S phase before returning to baseline before the onset of mitosis. The absence of the E2F1 3UTR in the constructs led to considerably higher steady-state levels of the fusion protein, which although normally regulated, exhibited a slightly less complex dynamic profile during the cell cycle or genotoxic stress. Lastly, the presence or absence of Rb failed to impact in substantial ways the overall detection and levels of the reporters.

cell biology↗