Biology subjects

Velickovic, M.

Publications and source records attributed to Velickovic, M..

8 recordsLinked to original sources

bioRxiv2026

Metabolites cross the membrane, the transcriptome does not follow: co-localization is required for the cyanobacterial response to a yeast partner

Interactions between phototrophs and heterotrophs are usually explained by cross-feeding, yet whether that exchange alone accounts for the phototroph's response has rarely been tested. We grew the sucrose-secreting cyanobacterium Synechococcus elongatus with the yeast Rhodotorula toruloides as a synthetic community, either in mixed co-culture or in membrane-separated co-culture (0.22 m pore size), each with a matched axenic control. Metabolite exchange occurred in both configurations: sucrose reached the yeast and was consumed, and yeast-derived metabolites reached the cyanobacterium. The yeast reached a higher final density behind the membrane, whereas the cyanobacterium gained about 9% over its axenic control only in mixed co-culture. Yet the cyanobacterial transcriptome responded only with co-localization: expression of 51 genes changed consistently across time points (day-averaged q < 0.05), against one gene behind the membrane, and the number of differentially expressed genes rose from 20 on day 4 to 91 and 127 on days 6 and 8. Nine regulatory programs (iModulons), mainly nitrogen and photosynthesis, responded in mixed co-culture and none behind the membrane. Reactor configuration alone changed 40 genes in axenic culture. These results suggest that co-localization, in addition to metabolite exchange, was required for the heterotrophic partner to trigger a response in the phototroph. Co-culture studies that infer interactions from shared metabolites may miss effects that depend on spatial structure. Importance Partnerships between light-powered microbes and the heterotrophs living alongside them move large amounts of carbon in oceans and soils, and are now built on purpose to turn carbon dioxide into fuels and chemicals. Such partnerships are usually described by the chemicals the partners trade, so we asked whether those chemicals are enough. The cyanobacterium Synechococcus elongatus and the yeast Rhodotorula toruloides were grown together in one vessel, or in two chambers divided by a membrane that molecules cross but cells cannot. The yeast fed on cyanobacterial sugar in both, yet the cyanobacterium changed its gene activity only when the two shared a space. Partners in nature are usually clustered rather than evenly mixed, so closeness may contribute as much as the chemicals themselves. Keeping partners apart in engineered cultures can still deliver carbon to the heterotroph, but may not deliver the benefits of partnership to the phototroph.

microbiology↗

bioRxiv2026

Characterization of the biofilm landscape of Bacillus subtilis by spatial microproteomics

Bulk proteomics has been demonstrated to differentiate subpopulations based on molecular phenotypes within bacterial colonies, yet advanced analyses by mass spectrometry imaging (MSI) hold even greater promise for the future. This technology can enable high-throughput spatial phenotyping that can directly visualize distinct components of various biomolecular mechanisms with high mass resolving power in high spatial resolution analyses. Here, we applied MSI for intact protein imaging directly from thin cross sections of a biofilm of Bacillus subtilis and after minimal preparation we detected more than 285 unique isotopic envelopes corresponding to unique proteoforms. We paired our MSI analyses with bulk top-down proteomics (TDP) to form extensive experimental libraries, which provided us with high confidence MSI annotations based upon isotopic matching to validated post-translational modifications (PTMs) and truncations. This joint application of MSI and TDP allowed us to describe the microscal e spatial proteomic landscape within the B. subtilis biofilm. This study further demonstrated the feasibility of detecting differentiated subpopulations of cells through the identification of proteoforms of cannibalistic protein toxins as well as those involved in active sporulation to highly localized areas within the central and outermost periphery of the biofilm. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=96 SRC="FIGDIR/small/702398v4_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@3fcd38org.highwire.dtl.DTLVardef@ba314dorg.highwire.dtl.DTLVardef@1faf52dorg.highwire.dtl.DTLVardef@f68974_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2024

Changes in maternal blood and placental lipidomic profile in obesity and gestational diabetes: Evidence for sexual dimorphism

IntroductionObesity and gestational diabetes (GDM) are associated with adverse pregnancy outcomes and program the offspring for cardiometabolic disease in a sexually dimorphic manner. The placenta transfers lipids to the fetus and uses these substrates to support its own metabolism impacting the amount of substrate available to the growing fetus. MethodsWe collected maternal plasma and placental villous tissue following elective cesarean section at term from women who were lean (pre-pregnancy BMI 18.5-24.9), obese (BMI>30) and type A2 GDM (matched to obese BMI) with male or female fetus (n=4 each group). Lipids were extracted and fatty acid composition of different lipid classes were analyzed by LC-MS/MS analysis. Significant changes in GDM vs obese, GDM vs lean, and obese vs lean were determined using t-test with a Tukey correction set at p<0.05. ResultsIn placental samples 436 lipids were identified, among which 85 showed significant changes. Of note only in male placentas significant decreases in C22:6 - docosahexaenoic acid (DHA) in phosphatidylcholine (PC) and triglyceride lipid species were seen when comparing tissue from GDM women to lean. In maternal plasma we observed no effect of obesity. GDM or fetal sex. ConclusionThis is the first study assessing fatty acid composition of lipids in matched maternal plasma and placental tissue from lean, obese, and GDM women stratified by fetal sex. It highlights how GDM affects distribution of fatty acids in lipid classes changes in a sexually dimorphic manner in the placenta.

molecular biology↗

bioRxiv2024

Spatial top-down proteomics for the functional characterization of human kidney

BackgroundThe Human Proteome Project has credibly detected nearly 93% of the roughly 20,000 proteins which are predicted by the human genome. However, the proteome is enigmatic, where alterations in amino acid sequences from polymorphisms and alternative splicing, errors in translation, and post-translational modifications result in a proteome depth estimated at several million unique proteoforms. Recently mass spectrometry has been demonstrated in several landmark efforts mapping the human proteoform landscape in bulk analyses. Herein, we developed an integrated workflow for characterizing proteoforms from human tissue in a spatially resolved manner by coupling laser capture microdissection, nanoliter-scale sample preparation, and mass spectrometry imaging. ResultsUsing healthy human kidney sections as the case study, we focused our analyses on the major functional tissue units including glomeruli, tubules, and medullary rays. After laser capture microdissection, these isolated functional tissue units were processed with microPOTS (microdroplet processing in one-pot for trace samples) for sensitive top-down proteomics measurement. This provided a quantitative database of 616 proteoforms that was further leveraged as a library for mass spectrometry imaging with near-cellular spatial resolution over the entire section. Notably, several mitochondrial proteoforms were found to be differentially abundant between glomeruli and convoluted tubules, and further spatial contextualization was provided by mass spectrometry imaging confirming unique differences identified by microPOTS, and further expanding the field-of-view for unique distributions such as enhanced abundance of a truncated form (1-74) of ubiquitin within cortical regions. ConclusionsWe developed an integrated workflow to directly identify proteoforms and reveal their spatial distributions. Where of the 20 differentially abundant proteoforms identified as discriminate between tubules and glomeruli by microPOTS, the vast majority of tubular proteoforms were of mitochondrial origin (8 of 10) where discriminate proteoforms in glomeruli were primarily hemoglobin subunits (9 of 10). These trends were also identified within ion images demonstrating spatially resolved characterization of proteoforms that has the potential to reshape discovery-based proteomics because the proteoforms are the ultimate effector of cellular functions. Applications of this technology have the potential to unravel etiology and pathophysiology of disease states, informing on biologically active proteoforms, which remodel the proteomic landscape in chronic and acute disorders.

biochemistry↗

bioRxiv2023

Robust collection and processing for label-free single voxel proteomics

With advanced mass spectrometry (MS)-based proteomics, genome-scale proteome coverage can be achieved from bulk tissues. However, such bulk measurement lacks spatial resolution and obscures important tissue heterogeneity, which make it impossible for proteome mapping of tissue microenvironment. Here we report an integrated wet collection of single tissue voxel and Surfactant-assisted One-Pot voxel processing method termed wcSOP for robust label-free single voxel proteomics. wcSOP capitalizes on buffer droplet-assisted wet collection of single tissue voxel dissected by LCM into the PCR tube cap and MS-compatible surfactant-assisted one-pot voxel processing in the collection cap. This convenient method allows reproducible label-free quantification of [~]900 and [~]4,600 proteins for single voxel from fresh frozen human spleen tissue at 20 m x 20 m x 10 m (close to single cells) and 200 m x 200 m x 10 m ([~]100 cells), respectively. 100s-1000s of protein signatures with differential expression levels were identified to be spatially resolved between spleen red and white pulp regions depending on the voxel size. Region-specific signaling pathways were enriched from single voxel proteomics data. Antibody-based CODEX imaging was used to validate label-free MS quantitation for single voxel analysis. The wcSOP-MS method paves the way for routine robust single voxel proteomics and spatial proteomics.

molecular biology↗

bioRxiv2023

Coupling microdroplet-based sample preparation, multiplexed isobaric labeling, and nanoflow peptide fractionation for deep proteome profiling of tissue microenvironment

There is increasing interest in developing in-depth proteomic approaches for mapping tissue heterogeneity at a cell-type-specific level to better understand and predict the function of complex biological systems, such as human organs. Existing spatially resolved proteomics technologies cannot provide deep proteome coverages due to limited sensitivity and poor sample recovery. Herein, we seamlessly combined laser capture microdissection with a low-volume sample processing technology that includes a microfluidic device named microPOTS (Microdroplet Processing in One pot for Trace Samples), the multiplexed isobaric labelling, and a nanoflow peptide fractionation approach. The integrated workflow allowed to maximize proteome coverage of laser-isolated tissue samples containing nanogram proteins. We demonstrated the deep spatial proteomics can quantify more than 5,000 unique proteins from a small-sized human pancreatic tissue pixel ([~]60,000 {micro}m2) and reveal unique islet microenvironments.

biochemistry↗

bioRxiv2022

Proteome mapping of the human pancreatic islet microenvironment reveals endocrine-exocrine signaling sphere of influence

The need for a clinically accessible method with the ability to match protein activity within heterogeneous tissues is currently unmet by existing technologies. Our proteomics sample preparation platform, named microPOTS (Microdroplet Processing in One pot for Trace Samples), can be used to measure relative protein abundance in micron-scale samples alongside the spatial location of each measurement, thereby tying biologically interesting proteins and pathways to distinct regions. However, given the smaller sample number and amount of tissue measu red, standard mass spectrometric analysis pipelines have proven inadequate. Here we describe how existing computational approaches can be adapted to focus on the specific biological questions asked in spatial proteomics experiments. We apply this approach to present an unbiased characterization of the human islet microenvironment comprising the entire complex array of tissues involved while maintaining spatial information and the degree of the islets sphere of influence. We identify specific functional activity unique to the pancreatic islet cells and demonstrate how far their signature can be measured. Our results show that we can distinguish pancreatic islet cells from the neighboring exocrine tissue environment, recapitulate known biological functions of islet cells, and identify a spatial gradient in the expression of RNA processing proteins within the islet microenvironment.

systems biology↗

bioRxiv2022

A streamlined tandem tip-based workflow for sensitive nanoscale phosphoproteomics

Effective phosphoproteome of nanoscale sample analysis remains a daunting task, primarily due to significant sample loss associated with non-specific surface adsorption during enrichment of low stoichiometric phosphopeptide. We developed a novel tandem tip phosphoproteomics sample preparation method that is capable of sample cleanup and enrichment without additional sample transfer, and its integration with our recently developed SOP (Surfactant-assisted One-Pot sample preparation) and iBASIL (improved Boosting to Amplify Signal with Isobaric Labeling) approaches provides a streamlined workflow enabling sensitive, high-throughput nanoscale phosphoproteome measurements. This approach significantly reduces both sample loss and processing time, allowing the identification of >3,000 (>9,500) phosphopeptides from 1 (10) {micro}g of cell lysate using the label-free method without a spectral library. It also enabled precise quantification of [~]600 phosphopeptides from 100 cells sorted by FACS (single-cell level input for the enriched phosphopeptides) and [~]700 phosphopeptides from human spleen tissue voxels with a spatial resolution of 200 {micro}m (equivalent to [~]100 cells) in a high-throughput manner. The new workflow opens avenues for phosphoproteome profiling of mass-limited samples at the low nanogram level.

biochemistry↗