Biology subjects

Levi, D.

Publications and source records attributed to Levi, D..

7 recordsLinked to original sources

bioRxiv2024

Profiling the physiological impact of aberrant folded-state protein filamentation in cells

The formation of large polymeric structures such as cytoskeletal and enzyme filaments is crucial for normal cellular function. However, such filaments can also form due to mutations that create self-interactions at the surface of symmetric proteins. Often, the proteins forming these structures maintain a folded state and thereby differ from aggregates and amyloids that involve misfolding. We refer to this type of assemblies as agglomerates to mark this difference. While cells have quality control mechanisms to identify, buffer, and eliminate misfolded proteins, it is unclear whether similar mechanisms exist for agglomerates, or whether agglomerates are toxic to cells. Here, we profiled the physiological impact of mutation-induced folded-state protein filamentation in yeast cells. First, we devised a simple strategy to distinguish fluorescently labeled proteins forming agglomerates versus aggregates. We then profiled exogenous protein agglomerates in terms of their recognition by known quality control mechanisms, their effects on specific cellular processes and overall fitness on S. cerevisiae cultures. We found that agglomerates do not colocalize with the proteostasis machinery and do not result in measurable fitness defects. Proteomics profiling of cells expressing the wild type protein, agglomerating or misfolded variants revealed a consistent picture, with only minor, agglomerate-size-dependent changes observed and linked to the cell-wall and plasma-membrane proteins. Overall, our findings indicate that agglomerates form mostly benign structures in cells when compared to aggregates, and thereby offer a promising route for synthetic biology applications. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=146 SRC="FIGDIR/small/612878v1_ufig1.gif" ALT="Figure 1"> View larger version (84K): org.highwire.dtl.DTLVardef@7136a4org.highwire.dtl.DTLVardef@ba62dborg.highwire.dtl.DTLVardef@b02bbaorg.highwire.dtl.DTLVardef@6cbf9_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

bioRxiv2023

Disproportion of reticulon-like 16 (RTNLB16) splice variants expression disrupts growth and decreases sensitivity to ABA and senescence in Arabidopsis

The Reticulon family proteins (RTNs) are membrane-spanning proteins found in the endoplasmic reticulum (ER) with diverse functions, such as ER membrane morphogenesis, vesicle formation, and trafficking. The plant-specific reticulon-like protein family (RTNLBs) comprises multiple members, yet their functions remain poorly understood. The Arabidopsis RTNLB16 gene has seven splice variants, each encoding seven distinct protein isoforms. We identified an Arabidopsis mutant (Salk_122275/rtnlb16-1) as a knockout for the upper coding frame, isoform 7, of RTNLB16 while overexpressing the other six isoforms through the CaMV 35S promoter at the left border of the T-DNA insertion. rtnlb16-1 exhibits distinctive growth retardation and reduced chlorophyll levels. Under photoperiodic long day (16:8 h) conditions, activation of the 35S promoter intensifies RTNLB16 expression in the mutant, resulting in profound growth inhibition. Conversely, growth under continuous low-light (CLL) conditions restrains the overexpression and significantly mitigates rtnlb16-1 phenotype. Confocal microscopy experiments revealed the localization of RTNLB16:GFP in the tubular ER network, plasmodesmata, and potentially in Golgi bodies. Peculiarly, RTLB16/rtnlb16 heterozygote plants exhibit non-Mendelian reduced fertility, suggesting potential involvement of RTNLB16 in reproductive development. Transcriptomics comparisons between rtnlb16-1 and the wild type under CLL and 16:8h conditions revealed differential gene expression involved in salicylic acid, jasmonic acid, and abscisic acid responses, indicating activation of defense and osmotic stress responses contributing to the growth inhibition in the mutant. We further demonstrate that rtnlb16 has decreased sensitivity to abscisic acid and enhanced tolerance to darkness-induced senescence. Our findings highlight the importance of balanced expression among RTNLB16 isoforms for normal cellular and physiological activities in Arabidopsis. Additionally, our study underscores the significance of employing T-DNA mutants to investigate genes with multiple splice variants.

plant biology↗

bioRxiv2023

Autotrophic growth of E. coli is achieved by a small number of genetic changes

Synthetic autotrophy is a promising avenue to sustainable bioproduction from CO2. Here, we use iterative laboratory evolution to generate several distinct autotrophic strains. Utilising this genetic diversity, we identify that just three mutations are sufficient for E. coli to grow autotrophically, when introduced alongside non-native energy (formate dehydrogenase) and carbon-fixing (RuBisCO, phosphoribulokinase, carbonic anhydrase) modules. The mutated genes are involved in glycolysis (pgi), central-carbon regulation (crp), and RNA transcription (rpoB). The pgi mutation reduces the enzymes activity, thereby stabilising the carbon-fixing cycle by capping a major branching flux. For the other two mutations, we observe down-regulation of several metabolic pathways and increased expression of native genes associated with the carbon-fixing module (rpiB) and the energy module (fdoGH), as well as an increased ratio of NADH/NAD+ - the cycles electron-donor. This study demonstrates the malleability of metabolism and its capacity to switch trophic modes using only a small number of genetic changes and could facilitate transforming other heterotrophic organisms into autotrophs.

synthetic biology↗

bioRxiv2023

Dichotomy of neutralizing antibody, B cell and T cell responses to SARS-CoV-2 vaccination and protection in healthy adults

Heterogeneity in SARS-CoV-2 vaccine responses is not understood. Here, we identify four patterns of live-virus neutralizing antibody responses: individuals with hybrid immunity (with confirmed prior infection); rare individuals with low responses (paucity of S1-binding antibodies); and surprisingly, two further groups with distinct serological repertoires. One group - broad responders - neutralize a range of SARS-CoV-2 variants, whereas the other - narrow responders - neutralize fewer, less divergent variants. This heterogeneity does not correlate with Ancestral S1-binding antibody, rather the quality of the serological response. Furthermore, IgDlowCD27-CD137+ B cells and CCR6+ CD4+ T cells are enriched in broad responders before dose 3. Notably, broad responders have significantly longer infection-free time after their third dose. Understanding the control and persistence of these serological profiles could allow personalized approaches to enhance serological breadth after vaccination.

immunology↗

bioRxiv2022

gUMI-BEAR, a modular, unsupervised population barcoding method to track variants and evolution at high resolution

Cellular lineage tracking provides a means to observe population makeup at the clonal level, allowing exploration of heterogeneity, evolutionary and developmental processes and individual clones relative fitness. It has thus contributed significantly to understanding microbial evolution, organ differentiation and cancer heterogeneity, among others. Its use, however, is limited because existing methods are highly specific, expensive, labour-intensive, and, critically, do not allow the repetition of experiments. To address these issues, we developed gUMI-BEAR (genomic Unique Molecular Identifier Barcoded Enriched Associated Regions), a modular, cost-effective method for tracking populations at high resolution. We first demonstrate the systems application and resolution by applying it to track tens of thousands of Saccharomyces cerevisiae lineages growing together under varying environmental conditions applied across multiple generations, revealing fitness differences and lineage-specific adaptations. Then, we demonstrate how gUMI-BEAR can be used to perform parallel screening of a huge number of randomly generated variants of the Hsp82 gene. We further show how our method allows isolation of variants, even if their frequency in the population is low, thus enabling unsupervised identification of modifications that lead to a behaviour of interest.

evolutionary biology↗

bioRxiv2021

Characterisation of tumour immune microenvironment remodelling following oncogene inhibition in preclinical studies using an optimised imaging mass cytometry workflow

Mouse models are critical in pre-clinical studies of cancer therapy, allowing dissection of mechanisms through chemical and genetic manipulations that are not feasible in the clinical setting. In studies of the tumour microenvironment (TME), multiplexed imaging methods can provide a rich source of information. However, the application of such technologies in mouse tissues is still in its infancy. Here we present a workflow for studying the TME using imaging mass cytometry with a panel of 27 antibodies on frozen mouse tissues. We optimise and validate image segmentation strategies and automate the process in a Nextflow-based pipeline (imcyto) that is scalable and portable, allowing for parallelised segmentation of large multi-image datasets. With these methods we interrogate the remodelling of the TME induced by a KRAS G12C inhibitor in an immune competent mouse orthotopic lung cancer model, highlighting the infiltration and activation of antigen presenting cells and effector cells.

cancer biology↗

bioRxiv2018

A bacterial growth law out of steady-state

Bacterial growth depends on numerous reactions, and yet follows surprisingly simple laws that inspired biologists for decades. Growth laws until now primarily dealt with steady-state exponential growth in constant conditions. However, bacteria in nature often face fluctuating environments, with nutritional upshifts and downshifts. We therefore ask whether there are growth laws that apply to changing environments. We derive a law for strong upshifts using an optimal resource-allocation model that was previously calibrated at steady-state growth: the post-shift growth rate equals the geometrical mean of the pre-shift growth rate and the growth rate on saturating carbon. We test this using chemostat and robotic batch culture experiments, as well as previous data from several species, and find good agreement with the model predictions. The increase in growth rate after an upshift indicates that ribosomes have spare capacity. We demonstrate theoretically that spare ribosomal capacity has the cost of slow steady-state growth, but is beneficial in fluctuating environments because it prevents large overshoots in intracellular metabolites after an upshift and allows rapid response to change. We also provide predictions for downshifts for future experimental tests. Spare capacity appears in diverse biological systems, and the present study quantifies the optimal degree of spare capacity, which rises the slower the growth rate, and suggests that it can be precisely regulated.

systems biology↗