Biology subjects

Zhu, Y.

Publications and source records attributed to Zhu, Y..

At least 361 records · Page 20Linked to original sources

bioRxiv2024

Development of a Two-Leaf Photosynthetic Model Sensitive to Chlorophyll and Its Coupling with a Wheat Growth Model

Crop growth models (CGMs) commonly simulates the response of photosynthetic rate to nitrogen (N) dynamic by calculating critical N concentration. However, critical N concentration makes it hard to describe the physiological effect of N dynamic on photosynthesis. Meanwhile, the effect of diffuse light on photosynthesis was limited in previous studies. In this study, we introduced a Two-leaf Photosynthetic Model Sensitive to Chlorophyll Content (TPMSCC) and coupled it with the crop growth model (WheatGrow) to enhance our understanding of how N dynamic and diffuse light affects photosynthesis. By coupling the Farquhar-von Caemmerer-Berry (FvCB) C3 photosynthesis model with a canopy radiative transfer model (PROSAIL), TPMSCC simulated the light interception of direct and diffuse light, and employed leaf chlorophyll content (LCC) to simulate the light absorption and electron transfer rate of leaves. Result showed that TPMSCC well simulated the light absorption of the wheat canopy and found the canopy photosynthetic rate benefited from the increase of diffuse radiation fraction (DRF) except for when the condition of a dense canopy at a high solar zenith angle was present. Research found the logarithmic and linear relationships of LCC to the initial light use efficiency ([a]) and the maximum photosynthetic rate (Amax), respectively, which followed the field measurements. Additionally, the optimized WheatGrow model outperforms its predecessor in describing the response of N application rate on photosynthesis.

biophysics↗

bioRxiv2024

Systematic Evaluation of Cell Type Deconvolution Methods for Plasma Cell-free DNA

Plasma cell-free DNA (cfDNA) is derived from cellular death in various tissues. Investigating the origin of cfDNA through tissue/cell type deconvolution allows us to detect changes in tissue homeostasis that occur during disease progression or in response to treatment. Consequently, cfDNA has emerged as a valuable noninvasive biomarker for disease detection and treatment monitoring. Although there are numerous methylation-based methods of cfDNA cell type deconvolution available, a comprehensive and systematic evaluation of these methods has yet to be conducted. In this study, we thoroughly benchmarked five previously published methods: MethAtlas, cfNOMe, CelFiE, CelFEER, and UXM. Utilizing deep whole-genome bisulfite sequencing data from 35 human cell types, we generated cfDNA mixtures with known ground truth to assess the deconvolution performance under various scenarios. Our findings indicate that different factors, including sequencing depth, reference marker selection, and reference completeness, influence cell type deconvolution performance. Notably, omitting cell types present in a mixture from the reference leads to suboptimal results. Despite each method exhibited distinct performances under various scenarios, CelFEER and UXM exhibit overall superior performance compared to the others. In summary, we comprehensively evaluated factors influencing methylation-based cfDNA cell type deconvolution and proposed general guidelines to maximize the performance.

bioinformatics↗

bioRxiv2024

Mechanical cues of extracellular matrix determines tumor innervation

Peripheral tumors can establish local autonomic and sensory nerve networks, termed as tumor innervation (TIN), to support tumorigenesis and metastasis. While nerve dependence in cancers is well-established, the mechanisms governing TIN remain unclear. Here, we report that extracellular matrix (ECM) stiffness, a major mechanical abnormality in the tumor microenvironment (TME), is an essential contributor of TIN. In preclinical models, reducing lysyl oxidase-mediated ECM crosslinking lowers tissue stiffness and TIN in pancreatic cancer, while inflammation-induced matrix stiffening boosts the hyperinnervation of the pancreatic precursor lesions. Mechanistically, {beta}1-containing integrins sense the mechanical cues exerted by ECM stiffness, and the translational co-activator YAP1 acts as an essential nuclear relay to induce the expression of neurotropic genes, particularly brain-derived neurotrophic factor (BDNF) and nerve growth factor (NGF). 3D imaging of the whole cleared pancreas reveals that blockade of mechanosensor integrin {beta}1 or pharmacological inhibition of the mechanotransducer YAP1 effectively reduces TIN. In clinical settings, tumor samples with a dense, crosslinked, and stiffened ECM exhibit significant TIN. In summary, these findings identify ECM stiffness as an important driver of TIN and suggest that targeting integrin {beta}1/YAP1-dependent mechanotransduction may counteract TIN.

neuroscience↗

bioRxiv2024

One signal activated TIL enable potent anti-tumor activity across diverse solid tumor types

Adoptive T cell therapy (ACT) is a promising therapeutic option that enhances the anti-cancer immune response to recognize and eliminate tumor burden. Recently, ACT modalities with autologous tumor-infiltrating lymphocytes (TILs) have shown robust anti-tumor efficacy in solid tumors. However, this therapeutic strategys application remains suboptimal in stability and faces critical challenges, primarily due to the lack of costimulatory signals. Here, we unveil a novel engineering strategy one-signal-activated TIL (OSAT), which integrates CD3{zeta} with secondary signaling domains, to bypass the classical dual-signal requirement for T cell activation. We demonstrate that OSAT molecules 2 (CD3{zeta}-CD28, M2) and 7 (CD3{zeta}-CD137-CD28, M7) mediate efficient mono-signal activation, and recapitulate both the activation signatures and functional markers of mock T cells stimulated with dual signals. Notably, OSAT exhibited enhanced cytotoxicity and in vivo anti-tumor activity across syngeneic tumor models, especially when combined with PD-1 blockade therapy. Mechanistically, OSAT can be fully activated by first signal stimulation, leading to upregulation of activation and metabolic reprogramming genes, production of IL-2/IFN-{gamma}/TNF-, initiation of cytotoxicity, and enhanced TIL antitumor efficacy. These findings unveil integrating CD3{zeta} with secondary signaling domains as a higher efficacy modification for TILs with therapeutic potential for clinical cancer immunotherapy.

immunology↗

bioRxiv2024

Development of quantitative high-throughput screening assays to identify, validate, and optimize small-molecule stabilizers of misfolded β-glucocerebrosidase with therapeutic potential for Gaucher disease and Parkinson's disease

Glucocerebrosidase (GCase) is implicated in both a rare, monogenic disorder (Gaucher disease, GD) and a common, multifactorial condition (Parkinsons disease); hence, it is an urgent therapeutic target. To identify correctors of severe protein misfolding and trafficking obstruction manifested by the pathogenic L444P-variant of GCase, we developed a suite of quantitative, high-throughput, cell-based assays. First, we labeled GCase with a small pro-luminescent HiBiT peptide reporter tag, enabling quantitation of protein stabilization in cells while faithfully maintaining target biology. TALEN-based gene editing allowed for stable integration of a single HiBiT-GBA1 transgene into an intragenic safe-harbor locus in GBA1-knockout H4 (neuroglioma) cells. This GD cell model was amenable to lead discovery via titration-based quantitative high-throughput screening and lead optimization via structure-activity relationships. A primary screen of 10,779 compounds from the NCATS bioactive collections identified 140 stabilizers of HiBiT-GCase-L444P, including both pharmacological chaperones (ambroxol and non-inhibitory chaperone NCGC326) and proteostasis regulators (panobinostat, trans-ISRIB, and pladienolide B). Two complementary high-content imaging-based assays were deployed to triage hits: the fluorescence-quenched substrate LysoFix-GBA captured functional lysosomal GCase activity, while an immunofluorescence assay featuring antibody hGCase-1/23 provided direct visualization of GCase lysosomal translocation. NCGC326 was active in both secondary assays and completely reversed pathological glucosylsphingosine accumulation. Finally, we tested the concept of combination therapy, by demonstrating synergistic actions of NCGC326 with proteostasis regulators in enhancing GCase-L444P levels. Looking forward, these physiologically-relevant assays can facilitate the identification, pharmacological validation, and medicinal chemistry optimization of new chemical matter targeting GCase, ultimately leading to a viable therapeutic for two protein-misfolding diseases. Significance StatementGaucher disease, the inherited deficiency of glucocerebrosidase, is caused by biallelic, loss-of-function mutations in the gene GBA1, which is also the most frequent genetic risk factor for Parkinsons disease. While the development of small-molecule stabilizers of glucocerebrosidase is being considered for both disorders, discovery and optimization of lead compounds is limited by the lack of robust cell-based assays amenable to high-throughput screening format. We developed a comprehensive assay pipeline for preclinical discovery of glucocerebrosidase modulators and began by screening libraries enriched with bioactive compounds with known mechanisms of action. The screen identified chemical matter with established relevance to glucocerebrosidase, provided an atlas of potential new molecular targets regulating the GBA1 pathway, and produced a set of promising potential therapeutics.

pharmacology and toxicology↗

bioRxiv2024

LncRNA-Snhg3 Aggravates Hepatic Steatosis by Regulating PPARγ via SND1/H3K27me3

LncRNAs are involved in modulating the individual risk and the severity of progression in metabolic dysfunction-associated fatty liver disease (MASLD), but their precise roles remain largely unknown. This study aimed to investigate the role of lncRNA Snhg3 in the development and progression of MASLD, along with the underlying mechanisms. The result showed that Snhg3 was significantly downregulated in the liver of high-fat diet-induced obesity (DIO) mice. Notably, palmitic acid promoted the expression of Snhg3 and overexpression of Snhg3 increased lipid accumulation in primary hepatocytes. Furthermore, hepatocyte-specific Snhg3 deficiency decreased body and liver weight, alleviated hepatic steatosis and promoted hepatic fatty acid metabolism in DIO mice, whereas overexpression induced the opposite effect. Mechanistically, Snhg3 promoted the expression, stability and nuclear localization of SND1 protein via interacting with SND1, thereby inducing K63-linked ubiquitination modification of SND1. Moreover, Snhg3 decreased the H3K27me3 level and induced SND1-mediated chromatin loose remodeling, thus reducing H3K27me3 enrichment at the Ppar{gamma} promoter and enhancing Ppar{gamma} expression. The administration of PPAR{gamma} antagonist T0070907 improved Snhg3-aggravated hepatic steatosis. Our study revealed a new signaling pathway, Snhg3/SND1/H3K27me3/PPAR{gamma}, responsible for MASLD and indicates that lncRNA-mediated epigenetic modification has a crucial role in the pathology of MASLD.

molecular biology↗

bioRxiv2024

Ca2+-independent ZmCPK2 is inhibited by Ca2+-dependent ZmCPK17 during drought response in maize

Calcium oscillations are induced by different stresses. Calcium-dependent protein kinases (CDPKs/CPKs) are one major group of the plant calcium decoders that are involved in various processes including drought response. Some CPKs are calcium-independent. Here, we identified ZmCPK2 as a negative regulator of drought resistance by screening an overexpression transgenic maize pool. We found that ZmCPK2 does not bind calcium, and its activity is modulated likely in an oscillation manner during short time ABA treatment. Interestingly, ZmCPK2 interacts with and is inhibited by calcium-dependent ZmCPK17, a positive regulator of drought resistance, which is activated by ABA. ZmCPK17 activity exhibits opposite patterns relative to ZmCPK2 under ABA treatment, and could prevent the nuclear localization of ZmCPK2 when co-expressed. ZmCPK2 interacts with and phosphorylates ZmYAB15, a negative transcriptional factor for drought resistance. Our results suggest that drought stress-induced Ca2+ can be decoded by corresponding CPK17 likely in an oscillation manner, thereby promoting plant adaptation to water deficit.

molecular biology↗

bioRxiv2024

Data Imbalance in Drug Response Prediction - Multi-Objective Optimization Approach in Deep Learning Setting

Drug response prediction (DRP) methods tackle the complex task of associating the effectiveness of small molecules with the specific genetic makeup of the patient. Anti-cancer DRP is a particularly challenging task requiring costly experiments as underlying pathogenic mechanisms are broad and associated with multiple genomic pathways. The scientific community has exerted significant efforts to generate public drug screening datasets, giving a path to various machine learning (ML) models that attempt to reason over complex data space of small compounds and biological characteristics of tumors. However, the data depth is still lacking compared to computer vision or natural language processing domains, limiting current learning capabilities. To combat this issue and increase the generalizability of the DRP models, we are exploring strategies that explicitly address the imbalance in the DRP datasets. We reframe the problem as a multi-objective optimization across multiple drugs to maximize deep learning model performance. We implement this approach by constructing Multi-Objective Optimization Regularized by Loss Entropy (MOORLE) loss function and plugging it into a Deep Learning model. We demonstrate the utility of proposed drug discovery methods and make suggestions for further potential application of the work to promote equitable outcomes in the healthcare field. Availabilityhttps://github.com/AlexandrNP/MOORLE Contactonarykov@anl.gov

cancer biology↗

bioRxiv2024

Information is asymmetry: spatial relations were encoded by asymmetric mnemonic manifolds

Substantial evidence suggests that working memory (WM) leverages relational representations to provide flexible support for cognitive functions, a capacity likely derived from the dynamic nature of neural codes in WM. However, how these dynamic codes represent and maintain relations remains unclear. Here, we examined the transformation of neural geometries in the dorsal prefrontal cortex of monkeys performing a visuospatial delayed-match/nonmatch task, where the monkeys were instructed to hold the spatial location of a white square in WM to match it with the spatial location of a subsequent square. We found that the sensory manifold during the squares presence and the mnemonic manifold after the squares offset both aligned with the stimulus manifold. However, significant differences emerged between the sensory and mnemonic manifolds, exhibiting little correlation in their neural geometries. Further analysis on the dynamic transformation from the sensory to mnemonic manifold revealed a process of expansion followed by flattening: the asymmetric sensory manifold first expanded into a symmetric neural geometry immediately after the squares onset offset, which then gradually flattened along dimensions different from those initially expanded, culminating in an asymmetric mnemonic manifold. This dynamic process of reconstruction not only remained its faithfulness to the stimulus geometry but also gained the flexibility to meet task demands. In sum, this transformation from asymmetry to symmetry and back to asymmetry in neural geometry precisely illustrates the dynamics of memory reconstruction, shedding lights on the subjective nature of WM that generates both accurate and illusory representation of the world we lived in.

neuroscience↗

bioRxiv2024

A brainstem circuit for gravity-guided vertical navigation

The sensation of gravity anchors our perception of the environment and is crucial for navigation. However, the neural circuits that transform gravity into commands for navigation are undefined. We first determined that larval zebrafish (Danio rerio) navigate vertically by maintaining a consistent heading across a series of upward climb or downward dive bouts. Gravity-blind mutant fish swim with more variable heading and excessive veering, leading to inefficient vertical navigation. After targeted photoablation of ascending vestibular neurons and spinal projecting midbrain neurons, but not vestibulospinal neurons, vertical navigation was impaired. These data define a sensorimotor circuit that uses evolutionarily-conserved brainstem architecture to transform gravitational signals into persistent heading for vertical navigation. The work lays a foundation to understand how vestibular inputs allow animals to move efficiently through their environment.

neuroscience↗

bioRxiv2024

Development of Broad-spectrum β-cyclodextrins-Based Nanomaterials Against Influenza Viruses

In recent decades, epidemics and pandemics have multiplied throughout the world, with viruses generally being the primary agents responsible. Among these, influenza viruses play a key role, as they cause severe respiratory distress, representing a major threat to public health. To enhance the response to viral disease outbreaks, there is a need for ready-to-use broad-spectrum antivirals. We have engineered macromolecules (named CD-SA) consisting of a {beta}-cyclodextrin (CD) scaffold modified with hydrophobic linkers in the primary face, onto which unitary sialic acid (SA) epitopes are covalently grafted, this to mimic influenza virus host receptors. In this study, we demonstrated that CD-SA, with a unitary SA, without extensive polysaccharides or specific connectivity, acts as a potent virucidal antiviral against several variants of human influenza type A and type B viruses. We also assessed the genetic barrier to resistance of CD-SA in vitro and successfully delayed emergence of resistance by combining CD-SA with interferon-{lambda}1 (IFN {lambda}1). Finally, we completed the characterization of the antiviral activity by conducting both ex vivo and in vivo studies, demonstrating a potent antiviral effect in human airway epithelia and in a mouse model of infection, higher than that of Oseltamivir, a currently approved anti-influenza antiviral.

microbiology↗

bioRxiv2024

Proteome-scale tissue mapping using mass spectrometry based on label-free and multiplexed workflows

Multiplexed bimolecular profiling of tissue microenvironment, or spatial omics, can provide deep insight into cellular compositions and interactions in healthy and diseased tissues. Proteome-scale tissue mapping, which aims to unbiasedly visualize all the proteins in a whole tissue section or region of interest, has attracted significant interest because it holds great potential to directly reveal diagnostic biomarkers and therapeutic targets. While many approaches are available, however, proteome mapping still exhibits significant technical challenges in both protein coverage and analytical throughput. Since many of these existing challenges are associated with mass spectrometry-based protein identification and quantification, we performed a detailed benchmarking study of three protein quantification methods for spatial proteome mapping, including label-free, TMT-MS2, and TMT-MS3. Our study indicates label-free method provided the deepest coverages of [~]3500 proteins at a spatial resolution of 50 {micro}m and the highest quantification dynamic range, while TMT-MS2 method holds great benefit in mapping throughput at >125 pixels per day. The evaluation also indicates both label-free and TMT-MS2 provide robust protein quantifications in identifying differentially abundant proteins and spatially co-variable clusters. In the study of pancreatic islet microenvironment, we demonstrated deep proteome mapping not only enables the identification of protein markers specific to different cell types, but more importantly, it also reveals unknown or hidden protein patterns by spatial co-expression analysis.

systems biology↗

bioRxiv2024

β-Hydroxybutyrate promotes basal insulin secretion while decreasing glucagon secretion in mouse and human islets.

Dietary carbohydrates raise blood glucose and limiting carbohydrate intake improves glycemia in patients with type 2 diabetes. Low carbohydrate intake (< 25 g) allows the body to utilize fat as its primary fuel. As a consequence of increased fatty acid oxidation, the liver produces ketones to serve as an alternative energy source. {beta}-Hydroxybutyrate ({beta}HB) is the most abundant ketone. While {beta}HB has a wide range of functions outside of the pancreas, its direct effects on islet cell function remain understudied. We examined human islet secretory response to acute racemic {beta}HB treatment and observed increased insulin secretion at low glucose concentrations (3 mM glucose). Because {beta}HB is a chiral molecule, existing as both R and S forms, we further studied insulin and glucagon secretion following acute treatment with individual {beta}HB enantiomers in human and C57BL6/J mouse islets. We found that acute treatment with R-{beta}HB increased insulin secretion and decreased glucagon secretion at physiological glucose concentrations in both human and mouse islets. Proteomic analysis of human islets treated with R-{beta}HB over 72 h showed altered abundance of proteins that may promote islet cell health and survival. Collectively, our data show that physiological concentrations of {beta}HB influence hormone secretion and signaling within pancreatic islets.

cell biology↗

bioRxiv2024

Unconventional IFNω-like genes dominate the type I IFN locus and the constitutive antiviral responses in bats

Bats are the natural reservoir hosts of some viruses, some of which may spillover to humans and cause global-scale pandemics. Different to humans, bats may coexist with high pathogenic viruses without showing symptoms of diseases. As one of the most important first defenses, bat type I interferon (IFN-Is) were thought to play a role during this virus coexistence and thus were studied in recent years. However, there are arguments that whether bats have a contracted genome locus or constitutive expressed IFNs, mainly due to species-specific findings. We hypothesized that because of the lacking of pan-bat analysis, the common characters for bat IFN-Is have not been revealed yet. Here, we characterized the IFN-I locus for 9 Yangochiroptera bats and 3 Yinpterochiroptera based on the their high quality bat genomes. We also compared the basal expression for 6 bats and compared the antiviral, anti-proliferative activity and thermo-stability of a representative Rhinolophus bat IFNs. We found a dominance of unconventional IFN{omega}-like responses in the IFN-I system, which is unique to bats. In contrast to IFNa-dominated IFN-I loci in the majority of other mammals, bats generally have shorter IFN-I loci with more unconventional IFN{omega}-like genes (IFN{omega} or related IFNa{omega}), but with less or even no IFNa genes. In addition, bats generally have constitutively expressed IFNs, the highest expressed of which is more likely an IFN{omega}-like gene. Likewise, the highly expressed IFN{omega}-like protein also demonstrated the best antiviral activity, anti-proliferative activity or thermo-stability, as shown in a representative Rhinolophus bat species. Overall, we revealed pan-bat unique characteristics in IFN-I system, which provide insights into our understanding of the innate immunity that contribute to a special coexistence between bats and viruses.

immunology↗

bioRxiv2024

From Sight to Insight: A Multi-task Approach with the Visual Language Decoding Model

Visual neural decoding aims to unlock the mysteries of how the human brain interprets the visual world. While early studies made some progress in decoding visual activity for singular type of information, they failed to concurrently reveal the multi-level interweaving linguistic information in the brain. Here, we developed a novel Visual Language Decoding Model (VLDM) capable of decoding categories, semantic labels, and textual descriptions from visual perceptual activities simultaneously. We selected the large-scale NSD dataset to ensure the efficiency of the decoding model in joint training and evaluation across multiple tasks. For category decoding, we achieved the effective classification of 12 categories with an accuracy of nearly 70%, significantly surpassing the chance level. For label decoding, we attained the precise prediction of 80 specific semantic labels with a 16-fold improvement over the chance level. For text decoding, the scores of the decoded text surpassed the corresponding baseline levels by remarkable margins on six evaluation metrics. This study contributes significantly to extensive applications in multi-layered brain-computer interfaces, potentially leading to more natural and efficient human-computer interaction experiences.

neuroscience↗

bioRxiv2024

Population genomics of the rice landrace Acuce reveals exceptional dynamics of immune receptors

In cultivated plants such as Oryza sativa, landraces harbour high levels of diversity, in sharp contrast with genetically uniform modern varieties. The Yuanyang terraces (China) are renowned for traditional farming involving landraces and low disease incidence. To understand the molecular basis of these resistance levels, we explored the genomic diversity of Acuce, one of the oldest landraces in the region. Based on whole-genome resequencing of over 200 Acuce plants, we evaluated the diversity of immunity and agronomical genes with respect to the rest of the genome. In parallel, we analysed the genetic basis of pathogen resistance and agronomical traits. Acuce exhibits high levels of diversity, reaching 38% of the worldwide levels. We uncovered an excess of diversity and signatures of directional selection associated with immunity genes, in contrast with agricultural traits. Furthermore, cultures of mixed genotypes exhibited superior performances for both pathogen resistance and agricultural traits. We showed that, within one single landrace, traditional farmer practices selected optimal agricultural traits while maintaining diversity enabling pathogen resistance. This study elucidates the complex interplay between genetic diversity, natural selection related to pathogens, and selection for agricultural traits within traditional landraces, providing insights into sustainable agricultural practices in diverse cropping systems.

genomics↗

bioRxiv2024

Ultraviolet attenuates centromere-mediated meiotic genome stability and alters gametophytic ploidy consistency in flowering plants

Ultraviolet (UV) radiation influences development and genome stability in organisms; however, its impacts on meiosis, a special cell division essential for the delivery of genetic information over generations in eukaryotes, remain not yet elucidated. In this study, we demonstrate that UV attenuates the centromere-mediated meiotic chromosome stability and induces unreduced gametes in Arabidopsis thaliana. We show that UV reduces crossover (CO) rate but does not interfere with meiotic chromosome integrity. Functional centromere-specific histone 3 (CENH3) is required for the obligate CO formation, and plays a role in protection of homolog synapsis and sister-chromatid cohesion under UV stress. Moreover, UV specifically alters the orientation and organization of spindles and phragmoplasts at meiosis II, resulting in meiotic restitution and unreduced gametes. Further, we determine that UV-induced meiotic restitution does not rely on the UV Resistance Locus8-mediated UV perception and the Tapetal Development and Function1- and Aborted Microspores-dependent tapetum development, but occurs possibly via impacted JASON function and downregulated Parallel Spindle1. This study sheds light on the impacts of UV on meiotic genome stability and gametophytic ploidy consistency, which thus may influence genome evolution in flowering plants.

plant 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↗