Biology subjects

Sorensen, M.

Publications and source records attributed to Sorensen, M..

9 recordsLinked to original sources

bioRxiv2026

Kinetic Lipidomics: Quantifying in vivo changes in lipid metabolism using metabolic labeling

Lipid metabolism reflects the dynamic balance between metabolic turnover and concentration. Kinetic mass spectrometry (MS) enables direct quantification of molecular turnover in vivo. Previous work has shown that MS-based kinetic proteomics has provided powerful insights into proteome regulation. Analogous lipidome-wide kinetic measurements remain limited by challenges in defining molecule-specific labeling behavior. Here, we extend kinetic MS to untargeted lipidomics. Isotope labeling with deuterated water (2H2O) is commonly used for monitoring turnover of palmitate and other select lipids by measuring labeling of stable C-H positions with deuterium (2H). Here, we extend the deuterium-incorporation model underlying these targeted lipid turnover assays to support untargeted analysis of all detectable lipids. This allows us to empirically quantify the effective fraction of endogenous synthesis (Asyn) and the turnover rate (k) across hundreds of lipid species simultaneously. One central barrier to lipidome-wide kinetic modeling is determining the endogenous number of deuterium-labeling sites for each molecule (nL) which is required to estimate Asyn and k accurately. The nL value is an essential component of biological kinetic assays. In kinetic proteomics, curated amino acid nL libraries enable peptide-level modeling by summing sequence-specific labeling-site values, but comparable resources are lacking for lipids and may not generalize across metabolic states or non-mammalian systems. Yet, gaps remain for lipids and for amino acids in modified metabolic conditions or non-mammalian biologies. Here, we empirically determine lipid nL values and validate the process with peptides against an nL library. To evaluate this strategy in a biologically relevant setting, we applied it to brain tissue from transgenic mice expressing human ApoE isoforms, where altered lipid transport and metabolism are implicated in Alzheimers disease risk. These data validate the method in a clinically relevant context and suggest that genotype-dependent metabolism can alter empirically determined lipid nL values.

biochemistry↗

bioRxiv2026

Ontological Analysis of Brain Proteostasis Highlights the Sex-Dependent Trajectory of ApoE Isoform-Specific Regulation

Apolipoprotein E (ApoE) is the strongest genetic predictor of Alzheimers disease (AD) risk, with ApoE4 increasing and ApoE2 decreasing risk relative to ApoE3. Using a global LC-MS proteomic approach, we integrated protein abundance and kinetics in Human-APOE knock-in mice for young (3-month) and aged (18-month) cohorts to quantify the changes in steady-state proteostasis. By mapping 6,052 identified proteins and 3,986 associated turnover rates into ontological groups, we observed that vesicle trafficking and mitochondrial dysregulation occur as early as 3 months in ApoE4 mice accompanied by hyperactive metabolism that eventually reduces with age. In contrast, young and old ApoE2 mice retain similar signatures to ApoE3 mice in metabolic, mitochondrial, cellular regulation, and membrane trafficking ontologies. We found that females had more isoform-induced ontological changes relative to ApoE3, providing insight into sex-dependent vulnerabilities. Our global proteomic approach for ApoE proteostasis crucially unifies independent literature observations while providing turnover kinetics to uncover the underlying mechanism behind abundance changes. Data are available via ProteomeXchange with identifier PXD079261. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=189 SRC="FIGDIR/small/735293v1_ufig2.gif" ALT="Figure 1000"> View larger version (45K): org.highwire.dtl.DTLVardef@28ebfforg.highwire.dtl.DTLVardef@9dc6f2org.highwire.dtl.DTLVardef@704577org.highwire.dtl.DTLVardef@e0b0e2_HPS_FORMAT_FIGEXP M_FIG C_FIG O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=139 SRC="FIGDIR/small/735293v1_ufig1.gif" ALT="Figure 1001"> View larger version (48K): org.highwire.dtl.DTLVardef@17d0474org.highwire.dtl.DTLVardef@af771borg.highwire.dtl.DTLVardef@1b49f67org.highwire.dtl.DTLVardef@14d3aa2_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2026

Proximity proteomics reveals a role for IFI16 during human coronavirus infection

Viruses rely on the infected host cell to ensure successful replication and propagation of infection. This is achieved through interactions between virus-encoded proteins and proteins expressed in infected cells. All human coronaviruses (HCoVs) encode 16 non-structural proteins (NSPs) which exhibit some level of similarity in identity and function among the HCoVs. To identify host proteins that are potential interacting partners of HCoV NSPs, we utilized split-TurboID along with mass spectrometry and identified IFN-{gamma}-inducible protein-16 (IFI16) as a proximal partner of SARS-CoV-2 NSP8 and NSP10. To investigate the significance of the association between the NSP8/NSP10 complex and IFI16, we utilized CRISPR-Cas9 to knockout and CRISPRi to knockdown IFI16 in A549 cells and demonstrated that loss or reduced expression of IFI16 leads to a decrease in human coronavirus infection. We further demonstrated that there is reduced viral RNA replication and viral protein synthesis upon loss of IFI16. Interestingly, the loss of IFI16 results in reduced expression of type I IFNs. Taken together, these data suggests that IFI16 promotes human coronavirus infection, and the role IFI16 plays in coronavirus replication is independent of its role as a regulator of type I IFN gene expression.

microbiology↗

bioRxiv2026

Donor-specific assemblies enhance somatic structural variant detection in complex genomic regions

Structural variants (SVs) contribute substantially to genomic variation and disease, but detecting somatic SVs (sSVs) remains difficult due to reference bias, mosaicism, and enrichment in repetitive regions. Linear reference genomes, like GRCh38 and CHM13, do not fully capture individual genomic structure, which can obscure true somatic variation. Donor-specific assemblies (DSAs) generated from the same genome where sSVs are being assayed provide a personalized alternative, yet their performance for sSV detection has not been systematically assessed. As part of the Somatic Mosaicism across Human Tissues (SMaHT) Network, we benchmark a DSA for sSV discovery in the COLO829 melanoma cell line with a matched normal sample from the same individual. We compare sSV detection across GRCh38, CHM13, and the COLO829BL_DSA using three different sSV callers (Delly, Severus, and Sniffles2) and sequence data from multiple long-read platforms. The COLO829BL_DSA identifies 1.8-fold more manually validated sSVs than linear references, in regions both shared with GRCh38 and CHM13 and unique to the COLO829BL_DSA. Variants detected only with the COLO829BL_DSA are often found in satellite and other repeat-rich regions that are difficult to resolve using standard references. In addition, several COLO829BL_DSA-specific sSVs are located in genes, some of which are associated with cancer. Overall, these results underscore the utility of DSAs in improving sSV detection.

genomics↗

bioRxiv2025

A molecular inventory of the faecal microbiomes of 23 marsupial species

Despite the recent expansion of culture-independent analyses of animal faecal microbiomes, many lineages remain understudied. Marsupials represent one such group, where despite their iconic status, direct sequencing-based analyses remain limited. Here we present a metagenomic and metabolomic exploration of the faecal microbiomes of 23 Diprotodontia marsupials, producing a reference set of 3,868 prokaryotic and 12,142 viral metagenome-assembled genomes, the majority (>80%) of which represent novel species. As with other animals, host phylogeny is the primary driver of microbiome composition, including distinct profiles for two eucalyptus folivore specialists (koalas and southern greater gliders), suggesting independent solutions to this challenging diet. Expansion of several bacterial and viral lineages were observed in these and other marsupial hosts that may provide adaptive benefits. Antimicrobial resistance genes were significantly more prevalent in captive than wild animals likely reflecting human interaction. This molecular dataset contributes to our ongoing understanding of animal faecal microbiomes. Impact statementDespite their ecological and evolutionary importance, marsupials remain underrepresented in microbiome research. Here, we present the most extensive faecal microbiome dataset to date for this group, encompassing metagenomic, metabolomic, and proximity ligation data from 23 marsupial species. As in other animals, we find the microbial community structure reflects the host species, and some marsupials carry expanded sets of certain microbial lineages indicative of within-host evolution. This work substantially expands the genomic landscape of host-associated microbes and viruses in a poorly studied mammalian clade. Data summaryRaw read data, prokaryotic MAGs [≥]50% complete with [≤]10% contamination are available via the European Nucleotide Archive under project PRJEB89408. The full set of viral genomes, clustered protein database and metabolite data (raw and processed) are available via https://doi.org/10.48610/14e37e9. Prokaryotic MAGs are also available via https://figshare.com/s/87443d80817f57aadc16.

microbiology↗

bioRxiv2025

Novel Computational Pipeline to Identify Target Sites for Broad Spectrum Antiviral Drugs

Emerging viruses pose an ongoing threat to human health. While certain viral families are common sources of outbreaks, predicting the specific virus within a family that will cause the next outbreak or pandemic is not possible, creating an urgent need for broad spectrum antiviral drugs that are effective against an array of related viral pathogens. However, broad spectrum drug development is hindered by the lack of detailed knowledge of compound binding sites that are structurally and functionally conserved between viral family members and are essential for virus replication. To overcome this limitation, we developed an in silico approach that combines AI-driven protein structure prediction, computational fragment soaking, multiple sequence alignment, and protein stability calculations to identify highly conserved target sites that are both solvent-accessible and conserved. We applied this approach to the Togaviridae family, which includes emerging pandemic disease threats such as chikungunya and Venezuelan equine encephalitis virus for which there are currently no approved antiviral therapies. Our analysis identified multiple solvent accessible and structurally conserved pockets in the alphavirus non-structural protein 2 (nsP2) protease domain, which is essential for processing of the viral replicase proteins. Mutagenesis of key solvent accessible and conserved residues identified novel pockets that are essential for protease activity and the replication of multiple alphaviruses, validating these pockets as potential antiviral target sites for nsP2 inhibitors. These findings highlight the potential of artificial intelligence-informed modeling for revealing functionally conserved, accessible pockets as a means of identifying potential target binding sites for broadly active direct acting antivirals. Significance StatementHere we present a novel integrative computational approach to identify novel target sites for broadly acting antiviral drugs. We used this technique to identify multiple functionally and structurally conserved protein surface pockets within the alphavirus nsP2 protease and methyl-transferase-like domain. Mutagenesis of these pockets identified that they are essential for protease activity and replication of a genetically diverse group of alphaviruses, validating these sites as potential targets for broadly active small molecule alphavirus inhibitors. This integrative AI-driven approach thus provides an important tool in developing antivirals essential for pandemic preparedness.

microbiology↗

bioRxiv2020

Rapid compensatory evolution can rescue low fitness symbioses following partner-switching

Partner-switching plays an important role in the evolution of symbiosis, enabling local adaptation and recovery from the breakdown of symbiosis. Because of intergenomic epistasis, partner-switched symbioses may possess novel combinations of phenotypes but may also exhibit low fitness due to their lack of recent coevolutionary history. Here, we examine the structure and mechanisms of intergenomic epistasis in the Paramecium-Chlorella symbiosis and test if compensatory evolution can rescue initially low fitness partner-switched symbioses. Using partner-switch experiments coupled with metabolomics we show evidence for intergenomic epistasis wherein low fitness arose from mismatched photoprotection traits and the resulting light stress experienced by non-native symbionts when in high light environments. Experimental evolution under high light conditions revealed that an initially low fitness partner-switched non-native host-symbiont pairing rapidly adapted, gaining fitness equivalent to the native host symbiont pairing in less than 50 host generations. Compensatory evolution took two alternative routes: Either, hosts evolved higher symbiont loads to mitigate for their new algal symbionts poor performance, or the algal symbionts themselves evolved higher investment in photosynthesis and photoprotective traits to better mitigate light stress. These findings suggest that partner-switching combined with rapid compensatory evolution will enable the recovery and local adaptation of symbioses in response to changing environments. Significance statementSymbiosis enables the formation of new organisms through the merger of once independent species. Through symbiosis, species can acquire new functions, driving evolutionary innovation and underpinning important ecosystem processes. Symbioses that breakdown due to changing environmental conditions can reform by acquiring new symbionts in a process called partner-switching but may exhibit low fitness due to their lack of coadaptation. Using a microbial symbiosis between the single-celled eukaryote Paramecium and the green alga Chlorella we show that low fitness in partner-switched host-symbiont pairings arises from mismatched photoprotection traits. However, such low fitness partner-switched pairings can be rapidly rescued by adaptive evolution, regaining high fitness in less than 50 host generations. Partner-switching coupled with rapid compensatory evolution can enable symbioses to recover from breakdown.

evolutionary biology↗

bioRxiv2019

A fully phased accurate assembly of an individual human genome

The prevailing genome assembly paradigm is to produce consensus sequences that "collapse" parental haplotypes into a consensus sequence. Here, we leverage the chromosome-wide phasing and scaffolding capabilities of single-cell strand sequencing (Strand-seq)1,2 and combine them with high-fidelity (HiFi) long sequencing reads3, in a novel reference-free workflow for diploid de novo genome assembly. Employing this strategy, we produce completely phased de novo genome assemblies separately for each haplotype of a single individual of Puerto Rican origin (HG00733) in the absence of parental data. The assemblies are accurate (QV > 40), highly contiguous (contig N50 > 25 Mbp) with low switch error rates (0.4%) providing fully phased single-nucleotide variants (SNVs), indels, and structural variants (SVs). A comparison of Oxford Nanopore and PacBio phased assemblies identifies 150 regions that are preferential sites of contig breaks irrespective of sequencing technology or phasing algorithms.

bioinformatics↗

bioRxiv2019

Efficient de novo assembly of eleven human genomes using PromethION sequencing and a novel nanopore toolkit

Present workflows for producing human genome assemblies from long-read technologies have cost and production time bottlenecks that prohibit efficient scaling to large cohorts. We demonstrate an optimized PromethION nanopore sequencing method for eleven human genomes. The sequencing, performed on one machine in nine days, achieved an average 63x coverage, 42 Kb read N50, 90% median read identity and 6.5x coverage in 100 Kb+ reads using just three flow cells per sample. To assemble these data we introduce new computational tools: Shasta - a de novo long read assembler, and MarginPolish & HELEN - a suite of nanopore assembly polishing algorithms. On a single commercial compute node Shasta can produce a complete human genome assembly in under six hours, and MarginPolish & HELEN can polish the result in just over a day, achieving 99.9% identity (QV30) for haploid samples from nanopore reads alone. We evaluate assembly performance for diploid, haploid and trio-binned human samples in terms of accuracy, cost, and time and demonstrate improvements relative to current state-of-the-art methods in all areas. We further show that addition of proximity ligation (Hi-C) sequencing yields near chromosome-level scaffolds for all eleven genomes.

bioinformatics↗