Biology subjects

Popovic, N.

Publications and source records attributed to Popovic, N..

5 recordsLinked to original sources

bioRxiv2026

Conserved emergent traits enable biobank-scale prediction of community function

Predicting the function of a microbial community from the identity of its members is a key goal of ecology and biotechnology. Here, we show that the systematic variation in how strains contribute to community function is phylogenetically conserved. This allows us to predict the collective function of communities solely from their member's taxonomic identity. Using soymilk fermentation as a model, we measured three industrially relevant functions - acidification, texture, sensory grade - across 307 synthetic communities combining 33 phylogenetically diverse lactic acid bacteria strains. The functional effect of a strain scaled linearly with the function of the receiving community, allowing us to summarize each strain's contribution across communities with two parameters, intercept and slope. These parameters were phylogenetically conserved, allowing us to impute their values for 17 previously unassayed strains, and use them to predict the three functions in 14 newly assembled communities. By redefining community function in terms of conserved emergent species traits, our results enable predictive engineering of microbial consortia at scale, and open a path towards genomic and evolutionary dissection of complex community phenotypes.

microbiology↗

bioRxiv2025

Reconstitution of glycan-driven MHC I recycling reveals calreticulin as mediator between TAPBPR and tapasin

Protein folding in the endoplasmic reticulum (ER) is essential for about one-third of the mammalian proteome. N-linked glycosylation and subsequent glycan remodeling barcodes glycoproteins during their maturation in the ER. Major histocompatibility complex class I (MHC I) molecules, key for adaptive immunity, rely on a dedicated quality control cycle that involves specialized chaperones and glycan-modifying enzymes for their maturation and loading of immunogenic peptides. However, the functional interplay of the MHC I editors tapasin as part of the peptide-loading complex (PLC), TAP-binding protein-related (TAPBPR), the UDP-glucose:glycoprotein glucosyltransferase 1 (UGGT1), and calreticulin in glycan-dependent transfer of MHC I clients has not been determined in a reconstituted system. With isolated components, we show that transfer of peptide-receptive MHC I from the downstream quality control factor TAPBPR back to tapasin depends on the recognition of the monoglucosylated glycan of MHC I by calreticulin. While calreticulins C-terminal acidic helix is dispensable for disengaging reglucosylated MHC I from TAPBPR, it is essential for docking MHC I onto tapasin. Our data provide a mechanistic basis for glycan-surveillance by calreticulin necessary for retrograde trafficking of misfolded or suboptimally loaded MHC I that escaped the first quality control at the PLC and were trapped by TAPBPR. Such finetuned dynamic network of glycan-dependent and MHC I-specific chaperones guarantees maturation of MHC I molecules and highlight the fundamental processes driving ER protein quality control. TeaserOur study dissects the mechanistic network of dedicated chaperones and glycan modifiers that quality-control MHC I. Significance StatementThe immune system relies on major histocompatibility complex (MHC) class I molecules to present protein fragments from within cells, enabling detection of infection or disease. This study uncovers how a dynamic, glycan-dependent chaperone network in the endoplasmic reticulum (ER) orchestrates the recycling of misfolded or suboptimally loaded MHC I. Using isolated components, the work shows how monoglucosylation of MHC I glycans by UDP-glucose:glycoprotein glucosyltransferase 1 (UGGT1) allows calreticulin to mediate transfer from the post-ER chaperone TAPBPR back to the ER-resident chaperone tapasin as part of the peptide-loading complex. These findings illuminate the coordinated action of TAPBPR, UGGT1, calreticulin, and tapasin-ERp57 in MHC I quality control, offering new insights in immune surveillance and how its disruption may contribute to disease.

immunology↗

bioRxiv2022

Modulation of nuclear and cytoplasmic mRNA fluctuations by time-dependent stimuli: analytical distributions

Temporal variation of environmental stimuli leads to changes in gene expression. Since the latter is noisy and since many reaction events occur between the birth and death of an mRNA molecule, it is of interest to understand how a stimulus affects the transcript numbers measured at various sub-cellular locations. Here, we construct a stochastic model describing the dynamics of signal-dependent gene expression and its propagation downstream of transcription. For any time-dependent stimulus and assuming bursty gene expression, we devise a procedure which allows us to obtain time-dependent distributions of mRNA numbers at various stages of its life-cycle, e.g. in its nascent form at the transcription site, post-splicing in the nucleus, and after it is exported to the cytoplasm. We also derive an expression for the error in the approximation whose accuracy is verified via stochastic simulation. We find that, depending on the frequency of oscillation and the time of measurement, a stimulus can lead to cytoplasmic amplification or attenuation of transcriptional noise.

systems biology↗

bioRxiv2020

Statistics of nascent and mature RNA fluctuations in a stochastic model of transcriptional initiation, elongation, pausing, and termination

Recent advances in fluorescence microscopy have made it possible to measure the fluctuations of nascent (actively transcribed) RNA. These closely reflect transcription kinetics, as opposed to conventional measurements of mature (cellular) RNA, whose kinetics is affected by additional processes downstream of transcription. Here, we formulate a stochastic model which describes promoter switching, initiation, elongation, premature detachment, pausing, and termination while being analytically tractable. By computational binning of the gene into smaller segments, we derive exact closed-form expressions for the mean and variance of nascent RNA fluctuations in each of these segments, as well as for the total nascent RNA on a gene. We also derive exact expressions for the first two moments of mature RNA fluctuations, and approximate distributions for total numbers of nascent and mature RNA. Our results, which are verified by stochastic simulation, uncover the explicit dependence of the statistics of both types of RNA on transcriptional parameters and potentially provide a means to estimate parameter values from experimental data.

systems biology↗

bioRxiv2018

Parameter inference with analytical propagators for stochastic models of autoregulated gene expression

Stochastic gene expression in regulatory networks is conventionally modelled via the Chemical Master Equation (CME). As explicit solutions to the CME, in the form of so-called propagators, are oftentimes not readily available, various approximations have been proposed. A recently developed analytical method is based on a separation of scales that assumes significant differences in the lifetimes of mRNA and protein in the network, allowing for the efficient approximation of propagators from asymptotic expansions for the corresponding generating functions. Here, we showcase the applicability of that method to simulated data from a telegraph model for gene expression that is extended with an autoregulatory mechanism. We demonstrate that the resulting approximate propagators can be applied successfully for Bayesian parameter inference in the non-regulated model; moreover, we show that, in the extended autoregulated model, autoactivation or autorepression may be refuted under certain assumptions on the model parameters. Our results indicate that the method showcased here may allow for successful parameter inference and model identification from longitudinal single cell data.

cell biology↗