Jaruffe Pinilla, A. | bioRxiv Science

bioRxiv2026

Longitudinal proteomic module configurations differ across human monocyte-derived differentiation and polarization conditions

Human monocyte differentiation involves changes in multiple protein programs, but comparisons across culture conditions can conflate source variation with differentiation time. We reanalyzed public proteomic measurements arranged in four source blocks across M1-polarizing, M2-polarizing, dendritic-cell and osteoclast conditions at days 2, 4, 6, 8 and 10. The original experiment used three individual-donor preparations and one preparation pooled from 40 donors; these are not four individual donors. Eight predefined protein-module scores formed an 80-observation matrix. A multivariate model tested joint condition and condition-by-time terms beyond source block and categorical time, using 9,999 permutations that preserved complete block-specific culture trajectories. The joint condition terms accounted for an additional 31.37% of total module-score variation (pseudo-F = 4.257567; permutation p = 0.0002). The association persisted after omission of each source block, with incremental R-squared of 0.315-0.390. Secondary day-specific tests detected differences at days 4-10, whereas day 2 did not meet the false-discovery criterion. Descriptive trajectories showed a shared increase in glycolysis/pentose-phosphate scores alongside condition-dependent mitochondrial, redox and proteostasis profiles. At day 10, M2-labelled cultures had the lowest mean mitochondrial score, whereas M1-labelled cultures had the highest three-protein resolution-associated score. All eight module tests survived multiplicity correction, and no single-module omission abolished the multivariate association. These findings describe condition-associated configurations within four heterogeneous source preparations. Equal weighting of source blocks does not estimate a mean across individual donors. The analysis does not establish pathway activity, single-cell trajectories, population-level replication or external biological validation.

immunology↗

bioRxiv2025

A Falsifiable Framework for Testing Neutralityin T-Cell Receptor Repertoire Databases

BackgroundT-cell receptor (TCR) repertoire databases aggregate antigen-specific sequences from hundreds of studies, exhibiting heavy-tailed occurrence distributions commonly interpreted as signatures of selection or criticality. However, distinguishing genuine non-neutral dynamics from neutral drift with realistic biological constraints requires explicit computational null models--currently absent from repertoire immunology. MethodsWe developed a biologically calibrated neutral null model incorporating thymic output, negative selection, and peripheral homeostasis with parameters independently derived from immunology literature (Robins et al. 2009, naive repertoires). The model was validated against empirical repertoire statistics before generating predictions. We compared neutral predictions to occurrence patterns from 24,847 TCR-epitope combinations in VDJdb across four viral targets using multi-observable testing (power-law exponent, Shannon entropy, public clonotype fraction) with Bonferroni-corrected thresholds. ResultsThe neutral null model successfully reproduced three independent benchmarks. Public clonotype fraction in VDJdb (3.10%) significantly exceeded neutral predictions (1.47%{+/-}0.29%, 100th percentile, p < 0.001, Cohens d = 5.62), inconsistent with neutrality at stringent thresholds (Bonferroni ' = 0.0167). In contrast, power-law exponent ( = 2.450 vs. 2.391 {+/-} 0.177, p = 0.739, d = 0.33) and Shannon entropy (H = 12.10 vs. 12.34 {+/-} 1.17 bits, p = 0.838, d = -0.21) showed negligible deviations. This dissociation--public fraction deviates while diversity metrics remain neutral-consistent--is consistent with but does not prove selective enrichment for cross-individual TCR convergence. Supplementary analyses confirmed public enrichment is temporally stable (2009-2024, no significant trend p > 0.40) and universal across viral pathogens (CMV, EBV, Influenza, SARS-CoV-2, ANOVA p > 0.68), constraining plausible curation bias mechanisms. ConclusionsWe present a rigorous falsificationist framework for testing neutrality in TCR repertoires via pre-validated computational nulls, multi-observable comparisons, and honest power reporting. Application to VDJdb reveals public clonotype patterns suggestive of non-neutral processes (functional selection or curation bias), establishing testable hypotheses for experimental follow-up. The framework--emphasizing independent validation, pre-specified decision criteria, and effect size quantification--generalizes to antibody repertoires, microbiomes, and evolutionary systems requiring mechanistic discrimination between drift and selection. Author SummaryDetermining whether T-cell receptor occurrence patterns arise from random drift or functional selection is fundamental to understanding adaptive immunity, yet current approaches rely on descriptive statistics rather than rigorous hypothesis testing. We developed the first falsifiable framework for testing neutrality in TCR databases using a biologically realistic computational null model validated against independent empirical benchmarks. Applying this framework to VDJdb, we find that public clonotype frequencies (sequences appearing across many individuals) deviate significantly from neutral predictions, while overall repertoire diversity remains consistent with neutrality. This pattern suggests--but does not definitively prove--that selection or curation bias operates specifically on cross-individual TCR convergence. Our contribution is methodological: we demonstrate how to test mechanistic hypotheses rigorously rather than describe patterns phenomenologically. The framework is immediately applicable to ongoing debates in repertoire immunology and generalizes to other biological systems exhibiting heavy-tailed distributions.

bioinformatics↗