Biology subjects

Bergstrom, E.

Publications and source records attributed to Bergstrom, E..

9 recordsLinked to original sources

bioRxiv2026

Adaptive energetic tuning of nucleolar phase separation regulates rRNA transport

Eukaryotic cells adjust biochemical pathways in response to environmental stressors, stalling energetically costly processes such as protein synthesis and ribosome biogenesis. Ribosome biogenesis occurs within the multiphase nucleolus that contains three layers roughly corresponding to ribosomal RNA (rRNA) transcription, processing, and assembly. While nucleolar perturbations induced by drug treatments and optogenetic nucleolar gelation alter nucleolar stability and hinder ribosome biogenesis, it remains unclear whether nucleolar properties are actively tuned in response to metabolic and growth cues. Here, we show that nucleolar phase separation is adjusted to physiological needs. Live-cell imaging of endogenously tagged NPM1 reveals a tight relationship between NPM1 partitioning and nutrient availability. In nutrient-deprived conditions, NPM1 levels in the nucleolus increase, indicative of stabilized phase separation and a more gel-like state. Indeed, we show that rRNA diffusion decreases and the nucleolar meshwork contracts. Furthermore, this change corresponds to decreased rRNA processing, suggesting that reduced transport properties prevent the release of immature ribosome subunits from the nucleolus. Mechanistically, we show that these changes are driven by ATP levels, which broadly affect the energetically expensive process of ribosome biogenesis. Upon restoration of ATP levels by nutrient reintroduction, nucleolar composition returns to normal within minutes, suggesting active regulation. Taken together, our findings reveal that the biophysical properties of the nucleolus are not fixed, but are actively remodeled by cellular energy levels, linking phase separation dynamics to metabolic control of ribosome biogenesis.

biophysics↗

bioRxiv2025

Chaotic behavior influenced by an environmental parameter in simulated C. elegans populations

Population dynamics can be chaotic when driven by internal feedback loops, including density-dependent mechanisms, making them predictable only for short periods of time. Since the first discovery of chaos in simple population models, many wild and laboratory populations have been characterized as chaotic. We ask whether a population simulation through a bottom-up modeling approach such as agent-based modeling can display chaotic dynamics. Here, we use wormPOP to simulate C. elegans population dynamics with changing culling parameters and calculate the largest Lyapunov Exponents of the simulated populations. The agent-based model wormPOP is a realistic simulation based on a laboratory population system with C. elegans and its food source E. coli. Our results show that depending on the percentage of culling, populations can exhibit chaotic or periodic behavior. Build-in randomization and the buffering of stress through alternative stress-resistant larva stages in C. elegans, complicates the analysis of wormPOP populations, however, the calculated LE for the identified chaotic conditions is robust to changing parameters in our analysis and fits expectations based on the scaling of LE with body size. In conclusion, agent-based models can generate realistic population dynamics that can be chaotic dependent on the chosen parameters.

ecology↗

bioRxiv2024

Comprehensive Evaluation of AlphaFold-Multimer, AlphaFold3 and ColabFold, and Scoring Functions in Predicting Protein-Peptide Complex Structures

Determining the three-dimensional structures of protein-peptide complexes is crucial for elucidating biological processes and designing peptide-based drugs. Protein-peptide docking has become essential for predicting complex structures. AlphaFold-Multimer, ColabFold and AlphaFold3 provided groundbreaking tools to enhance the protein-peptide docking accuracy. This study evaluates these three tools for predicting protein-peptide complex structures using Template-Based (TB) and Template-Free (TF) methods. AlphaFold-Multimer excels in TB predictions and performs moderately in TF scenarios in the prediction pool, but TF outperforms TB in the first-ranked models. ColabFold demonstrates versatility in both TB and TF settings. AlphaFold3 generates high-quality structures for more proteins, but the medium accuracy is not as good as AlphaFold-Multimer using a large model pool. We also assessed the performance of various scoring functions in ranking predicted protein-peptide complex structures. While the scoring function built in AlphaFold demonstrates the best performance, some other scoring functions, e.g., FoldX-Stability and HADDOCK-mdscore, provide complementary values. The findings suggest the potential for enhancing scoring functions targeting AlphaFold-based predictions by combining multiple scoring functions or using a consensus approach from many prediction models.

bioinformatics↗

bioRxiv2024

APOBEC shapes tumor evolution and age at onset of lung cancer in smokers

APOBEC enzymes are part of the innate immunity and are responsible for restricting viruses and retroelements by deaminating cytosine residues1,2. Most solid tumors harbor different levels of somatic mutations attributed to the off-target activities of APOBEC3A (A3A) and/or APOBEC3B (A3B)3-6. However, how APOBEC3A/B enzymes shape the tumor evolution in the presence of exogenous mutagenic processes is largely unknown. Here, by combining deep whole-genome sequencing with multi-omics profiling of 309 lung cancers from smokers with detailed tobacco smoking information, we identify two subtypes defined by low (LAS) and high (HAS) APOBEC mutagenesis. LAS are enriched for A3B-like mutagenesis and KRAS mutations, whereas HAS for A3A-like mutagenesis and TP53 mutations. Unlike APOBEC3A, APOBEC3B expression is strongly associated with an upregulation of the base excision repair pathway. Hypermutation by unrepaired A3A and tobacco smoking mutagenesis combined with TP53-induced genomic instability can trigger senescence7, apoptosis8, and cell regeneration9, as indicated by high expression of pulmonary healing signaling pathway, stemness markers and distal cell-of-origin in HAS. The expected association of tobacco smoking variables (e.g., time to first cigarette) with genomic/epigenomic changes are not observed in HAS, a plausible consequence of frequent cell senescence or apoptosis. HAS have more neoantigens, slower clonal expansion, and older age at onset compared to LAS, particularly in heavy smokers, consistent with high proportions of newly generated, unmutated cells and frequent immuno-editing. These findings show how heterogeneity in mutational burden across co-occurring mutational processes and cell types contributes to tumor development, with important clinical implications.

genomics↗

bioRxiv2024

Rare SNP in the HELB gene interferes with RPA interaction and cellular function of HELB

HELB is a human helicase involved in initiation of DNA replication, the replication stress response, and regulation of double-strand DNA break repair. rs75770066 is a rare SNP in the HELB gene that affects age at natural menopause. rs75770066 results in a D506G substitution in an acidic patch within the 1A domain of the helicase that is known to interact with RPA. We found that this amino acid change dramatically impairs the cellular function of HELB. D506G-HELB exhibits impaired interaction with RPA, which likely results in the effects of rs75770066 as this reduces recruitment of HELB to sites of DNA damage. Reduced recruitment of D506G-HELB to double-strand DNA breaks and the concomitant increase in homologous recombination likely alters the levels of meiotic recombination, which affects the viability of gametes. Because menopause occurs when oocyte levels drop below a minimum threshold, altered repair of meiotic double-stranded DNA breaks has the potential to directly affect the age at natural menopause.

biochemistry↗

bioRxiv2022

Formation of sulfoquinovosyl diacylglycerol by acylation of sulfoquinovosyl glycerol

Sulfoquinovosyl diacylglycerol (SQDG) is a membrane-forming lipid present in photosynthetic organisms as well as in distinct bacteria growing in phosphate-limited environments. Four genes for SQDG biosynthesis were previously identified in Rhodobacter sphaeroides, the operon sqdBDC and sqdA. In this work, we found that SMc02490 of Sinorhizobium meliloti is an SqdA orthologue. Expression of the S. meliloti sqdBDC operon in Escherichia coli results in formation of sulfoquinovosyl glycerol (SQGro), while co-expression of this operon together with smc02490 (sqdA) results in formation of SQDG. Furthermore, SqdA allows for incorporation of exogenous SQGro into SQDG in S. meliloti and in E. coli cultures, suggesting that presence of SqdA in bacteria permit them to use environmental SQGro for the biosynthesis of the membrane lipid SQDG. An in vitro enzymatic assay for the acyltransferase SqdA was developed. Cell-free crude extracts of E. coli expressing sqdA can efficiently convert [35S]-sulfoquinovosyl monoacylglycerol into SQDG using as acyl donor acyl carrier protein. Bioinformatic analyses reveal that this sulfoquinovose acylation pathway for SQDG biosynthesis is delimited to the Hyphomicrobiales (Rhizobiales) and Rhodobacterales orders of Alphaproteobacteria.

microbiology↗

bioRxiv2022

Single-cell genome-wide association reveals a nonsynonymous variant in ERAP1 confers increased susceptibility to influenza virus

Diversity in the human genome is one factor that confers resistance and susceptibility to infectious diseases. This is observed most dramatically during pandemics, where individuals exhibit large differences in risk and clinical outcomes against a pathogen infecting large portions of the worlds populations. Here, we developed scHi-HOST (single cell High-throughput Human in vitrO Susceptibility Testing), a method for rapidly identifying genetic variants that confer resistance and susceptibility to pathogens. scHi-HOST leverages scRNA-seq (single-cell RNA-sequencing) to simultaneously assign genetic identity to individual cells in mixed infections of cell lines of European, African, and Asian origin, reveal associated genetic variants for viral entry and replication, and identify expression quantitative trait loci (eQTLs). Applying scHi-HOST to influenza A virus (IAV), we identified eQTLs at baseline and in genes that are induced by IAV infection. Integration of scHi-HOST with a human IAV challenge study (Prometheus) revealed that a missense variant in ERAP1 (Endoplasmic reticulum aminopeptidase 1; rs27895) was associated with IAV burden in cells and human volunteers. Functional studies using RNA interference, ERAP1 inhibitor, and overexpression of alternative alleles demonstrated that ERAP1 is exploited by IAV to promote infection. Specifically, the nonsynonymous substitution, which results in a glycine to aspartate substitution at ERAP1 residue 348, would disrupt the substrate binding pocket of ERAP1, likely resulting in a significantly altered preference for substrates, poorer catalytic efficiency, or both. Finally, rs27895 exhibits substantial population differentiation, with the higher frequency of the minor T allele in two African populations likely contributing to the greater permissivity of cells from these populations to IAV infection. scHi-HOST is an important resource for understanding susceptibility to influenza and is a broadly applicable method for decoding human genetics of infectious disease.

genetics↗

bioRxiv2021

Disentangling heterogeneity of Malignant Pleural Mesothelioma through deep integrative omics analyses

Malignant Pleural Mesothelioma (MPM) is an aggressive cancer with rising incidence and challenging clinical management. Using the largest series of whole-genome sequencing data integrated with transcriptomic and epigenomic data using multi-omic factor analysis, we demonstrate that MPM heterogeneity arises from four sources of variation: tumor cell morphology, ploidy, adaptive immune response, and CpG island methylator phenotype. Previous genomic studies focused on describing only the tumor cell morphology factor, although we robustly find the three other sources in all publicly available cohorts. We prove how these sources of variation explain the biological functions performed by the cancer cells, and how genomic events shape MPM molecular profiles. We show how these new sources of variation help understand the heterogeneity of the clinical behavior of MPM and drug responses measured in cell lines. These findings unearth the interplay between MPM functional biology and its genomic history, and ultimately, inform classification, prognostication and treatment. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/461908v1_ufig1.gif" ALT="Figure 1"> View larger version (44K): org.highwire.dtl.DTLVardef@b6c43corg.highwire.dtl.DTLVardef@10d45a9org.highwire.dtl.DTLVardef@58746eorg.highwire.dtl.DTLVardef@143f880_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2018

The Repertoire of Mutational Signatures in Human Cancer

Somatic mutations in cancer genomes are caused by multiple mutational processes each of which generates a characteristic mutational signature. Using 84,729,690 somatic mutations from 4,645 whole cancer genome and 19,184 exome sequences encompassing most cancer types we characterised 49 single base substitution, 11 doublet base substitution, four clustered base substitution, and 17 small insertion and deletion mutational signatures. The substantial dataset size compared to previous analyses enabled discovery of new signatures, separation of overlapping signatures and decomposition of signatures into components that may represent associated, but distinct, DNA damage, repair and/or replication mechanisms. Estimation of the contribution of each signature to the mutational catalogues of individual cancer genomes revealed associations with exogenous and endogenous exposures and defective DNA maintenance processes. However, many signatures are of unknown cause. This analysis provides a systematic perspective on the repertoire of mutational processes contributing to the development of human cancer including a comprehensive reference set of mutational signatures in human cancer.

cancer biology↗