Single-Cell Proteomics Analysis with Tecan Uno and SCREEN Workflow.

With advances in sample preparation, small-volume liquid dispensing technologies, high-resolution MS/MS instrumentation, and data acquisition methodologies, it has become increasingly possible to confidently investigate the heterogeneous proteome found within individual cells. In this chapter, we present an automated high-throughput sample preparation workflow based on the Tecan Uno instrument for quantitative single-cell mass spectrometry-based proteomics. Cells are analyzed by the Single-Cell Proteome Analysis platform (SCREEN), which was introduced earlier and provides deeper proteome coverage across single cells.

A blood-brain barrier-penetrant AAV gene therapy improves neurological function in symptomatic mucolipidosis IV mice.

Mucolipidosis IV (MLIV) is a rare, autosomal recessive, lysosomal disease characterized by intellectual disability, motor deficits, and progressive vision loss. Using adeno-associated vector 9 (AAV9) and AAV-PHP.B as delivery vectors, we previously demonstrated the feasibility of modifying disease course in a mouse model of MLIV by the human MCOLN1 gene transfer. Here, using a primate-enabling capsid AAV.CPP.16 (CPP16), we constructed a new, clinic-oriented MCOLN1 gene expression vector and demonstrated its efficacy in the preclinical model of MLIV. Systemic administration of CPP16-MCOLN1 in adult symptomatic Mcoln1 -/- mice at a dose of 1e12 vg per mouse resulted in MCOLN1 expression in the brain and peripheral tissues, alleviated brain pathology, rescued neuromotor function, and completely prevented paralysis. Notable expression of MCOLN1 transcripts was also detected in the retina of the mouse, which had exhibited significant degeneration at the time of the treatment. However, no increase in retinal thickness was observed after gene therapy treatment. Our results suggest a new AAV-based systemic gene replacement therapy for the treatment of MLIV that could be translated into clinical studies.

Synthetic genomes unveil the effects of synonymous recoding.

Engineering the genetic code of an organism provides the basis for (i) making any organism safely resistant to natural viruses and (ii) preventing genetic information flow into and out of genetically modified organisms while (iii) allowing the biosynthesis of genetically encoded unnatural polymers1-4. Achieving these three goals requires the reassignment of multiple of the 64 codons nature uses to encode proteins. However, synonymous codon replacement-recoding-is frequently lethal, and how recoding impacts fitness remains poorly explored. Here, we explore these effects using whole-genome synthesis, multiplexed directed evolution, and genome-transcriptome-translatome-proteome co-profiling on multiple recoded genomes. Using this information, we assemble a synthetic Escherichia coli genome in seven sections using only 57 codons to encode proteins. By discovering the rules responsible for the lethality of synonymous recoding and developing a data-driven multi-omics-based genome construction workflow that troubleshoots synthetic genomes, we overcome the lethal effects of 62,007 synonymous codon swaps and 11,108 additional genomic edits. We show that synonymous recoding induces transcriptional noise including new antisense RNAs, leading to drastic transcriptome and proteome perturbation. As the elimination of select codons from an organism's genetic code results in the widespread appearance of cryptic promoters, we show that synonymous codon choice may naturally evolve to minimize transcriptional noise. Our work provides the first genome-scale description of how synonymous codon changes influence organismal fitness and paves the way for the construction of functional genomes that provide genetic firewalls from natural ecosystems and safely produce biopolymers, drugs, and enzymes with an expanded chemistry.

Mucus production, host-microbiome interactions, hormone sensitivity, and innate immune responses modeled in human cervix chips.

Modulation of the cervix by steroid hormones and commensal microbiome play a central role in the health of the female reproductive tract. Here we describe organ-on-a-chip (Organ Chip) models that recreate the human cervical epithelial-stromal interface with a functional epithelial barrier and production of mucus with biochemical and hormone-responsive properties similar to living cervix. When Cervix Chips are populated with optimal healthy versus dysbiotic microbial communities (dominated by Lactobacillus crispatus and Gardnerella vaginalis, respectively), significant differences in tissue innate immune responses, barrier function, cell viability, proteome, and mucus composition are observed that are similar to those seen in vivo. Thus, human Cervix Organ Chips represent physiologically relevant in vitro models to study cervix physiology and host-microbiome interactions, and hence may be used as a preclinical testbed for development of therapeutic interventions to enhance women's health.

Symmetry in levels of axon-axon homophilic adhesion establishes topography in the corpus callosum and development of connectivity between brain hemispheres.

Specific and highly diverse connectivity between functionally specialized regions of the nervous system is controlled at multiple scales, from anatomically organized connectivity following macroscopic axon tracts to individual axon target-finding and synapse formation. Identifying mechanisms that enable entire subpopulations of related neurons to project their axons with regional specificity within stereotyped tracts to form appropriate long-range connectivity is key to understanding brain development, organization, and function. Here, we investigate how axons of the cerebral cortex form precise connections between the two cortical hemispheres via the corpus callosum. We identify topographic principles of the developing trans-hemispheric callosal tract that emerge through intrinsic guidance executed by growing axons in the corpus callosum within the first postnatal week in mice. Using micro-transplantation of regionally distinct neurons, subtype-specific growth cone purification, subcellular proteomics, and in utero gene manipulation, we investigate guidance mechanisms of transhemispheric axons. We find that adhesion molecule levels instruct tract topography and target field guidance. We propose a model in which transcallosal axons in the developing brain perform a "handshake" that is guided through co-fasciculation with symmetric contralateral axons, resulting in the stereotyped homotopic connectivity between the brain's hemispheres.

Single cell proteomics analysis of drug response shows its potential as a drug discovery platform.

Single-cell analysis has clearly established itself in biology and biomedical fields as an invaluable tool that allows one to comprehensively understand the relationship between cells, including their types, states, transitions, trajectories, and spatial position. Scientific methods such as fluorescence labeling, nanoscale super-resolution microscopy, advances in single cell RNAseq and proteomics technologies, provide more detailed information about biological processes which were not evident with the analysis of bulk material. This new era of single-cell biology provides a better understanding of such complex biological systems as cancer, inflammation, immunity mechanism and aging processes, and opens the door into the field of drug response heterogeneity. The latest discoveries of cellular heterogeneity gives us a unique understanding of complex biological processes, such as disease mechanism, and will lead to new strategies for better and personalized treatment strategies. Recently, single-cell proteomics techniques that allow quantification of thousands of proteins from single mammalian cells have been introduced. Here we present an improved single-cell mass spectrometry-based proteomics platform called SCREEN (Single Cell pRotEomE aNalysis) for deep and high-throughput single-cell proteome coverage with high efficiency, less turnaround time and with an improved ability for protein quantitation across more cells than previously achieved. We applied this new platform to analyze the single-cell proteomic landscape under different drug treatment over time to uncover heterogeneity in cancer cell response, which for the first time, to our knowledge, has been achieved by mass spectrometry based analytical methods. We discuss challenges in single-cell proteomics, future improvements and general trends with the goal to encourage forthcoming technical developments.

Brain cell type specific proteomics approach to discover pathological mechanisms in the childhood CNS disorder mucolipidosis type IV.

Mucolipidosis IV (MLIV) is an ultra-rare, recessively inherited lysosomal disorder resulting from inactivating mutations in MCOLN1, the gene encoding the lysosomal cation channel TRPML1. The disease primarily affects the central nervous system (CNS) and manifests in the first year with cognitive and motor developmental delay, followed by a gradual decline in neurological function across the second decade of life, blindness, and premature death in third or fourth decades. Brain pathology manifestations in MLIV are consistent with hypomyelinating leukodystrophy with brain iron accumulation. Presently, there are no approved or investigational therapies for MLIV, and pathogenic mechanisms remain largely unknown. The MLIV mouse model, Mcoln1-/- mice, recapitulates all major manifestations of the human disease. Here, to better understand the pathological mechanisms in the MLIV brain, we performed cell type specific LC-MS/MS proteomics analysis in the MLIV mouse model and reconstituted molecular signatures of the disease in either freshly isolated populations of neurons, astrocytes, oligodendrocytes, and neural stem cells, or whole tissue cortical homogenates from young adult symptomatic Mcoln1-/- mice. Our analysis confirmed on the molecular level major histopathological hallmarks of MLIV universally present in Mcoln1-/- tissue and brain cells, such as hypomyelination, lysosomal dysregulation, and impaired metabolism of lipids and polysaccharides. Importantly, pathway analysis in brain cells revealed mitochondria-related alterations in all Mcoln1-/- brain cells, except oligodendrocytes, that was not possible to resolve in whole tissue. We also report unique proteome signatures and dysregulated pathways for each brain cell population used in this study. These data shed new light on cell-intrinsic mechanisms of MLIV and provide new insights for biomarker discovery and validation to advance translational studies for this disease.

A review of the current state of single-cell proteomics and future perspective.

Single-cell methodologies and technologies have started a revolution in biology which until recently has primarily been limited to deep sequencing and imaging modalities. With the advent and subsequent torrid development of single-cell proteomics over the last 5 years, despite the fact that proteins cannot be amplified like transcripts, it has now become abundantly clear that it is a worthy complement to single-cell transcriptomics. In this review, we engage in an assessment of the current state of the art of single-cell proteomics including workflow, sample preparation techniques, instrumentation, and biological applications. We investigate the challenges associated with working with very small sample volumes and the acute need for robust statistical methods for data interpretation. We delve into what we believe is a promising future for biological research at single-cell resolution and highlight some of the exciting discoveries that already have been made using single-cell proteomics, including the identification of rare cell types, characterization of cellular heterogeneity, and investigation of signaling pathways and disease mechanisms. Finally, we acknowledge that there are a number of outstanding and pressing problems that the scientific community vested in advancing this technology needs to resolve. Of prime importance is the need to set standards so that this technology becomes widely accessible allowing novel discoveries to be easily verifiable. We conclude with a plea to solve these problems rapidly so that single-cell proteomics can be part of a robust, high-throughput, and scalable single-cell multi-omics platform that can be ubiquitously applied to elucidating deep biological insights into the diagnosis and treatment of all diseases that afflict us.

Systematic conformation-to-phenotype mapping via limited deep sequencing of proteins.

Non-native conformations drive protein-misfolding diseases, complicate bioengineering efforts, and fuel molecular evolution. No current experimental technique is well suited for elucidating them and their phenotypic effects. Especially intractable are the transient conformations populated by intrinsically disordered proteins. We describe an approach to systematically discover, stabilize, and purify native and non-native conformations, generated in vitro or in vivo, and directly link conformations to molecular, organismal, or evolutionary phenotypes. This approach involves high-throughput disulfide scanning (HTDS) of the entire protein. To reveal which disulfides trap which chromatographically resolvable conformers, we devised a deep-sequencing method for double-Cys variant libraries of proteins that precisely and simultaneously locates both Cys residues within each polypeptide. HTDS of the abundant E. coli periplasmic chaperone HdeA revealed distinct classes of disordered hydrophobic conformers with variable cytotoxicity depending on where the backbone was cross-linked. HTDS can bridge conformational and phenotypic landscapes for many proteins that function in disulfide-permissive environments.

Improved isolation of extracellular vesicles by removal of both free proteins and lipoproteins.

Extracellular vesicles (EVs) are released by all cells into biofluids such as plasma. The separation of EVs from highly abundant free proteins and similarly sized lipoproteins remains technically challenging. We developed a digital ELISA assay based on Single Molecule Array (Simoa) technology for ApoB-100, the protein component of several lipoproteins. Combining this ApoB-100 assay with previously developed Simoa assays for albumin and three tetraspanin proteins found on EVs (Ter-Ovanesyan, Norman et al., 2021), we were able to measure the separation of EVs from both lipoproteins and free proteins. We used these five assays to compare EV separation from lipoproteins using size exclusion chromatography with resins containing different pore sizes. We also developed improved methods for EV isolation based on combining several types of chromatography resins in the same column. We present a simple approach to quantitatively measure the main impurities of EV isolation in plasma and apply this approach to develop novel methods for enriching EVs from human plasma. These methods will enable applications where high-purity EVs are required to both understand EV biology and profile EVs for biomarker discovery.

Integration of a multi-omics stem cell differentiation dataset using a dynamical model.

Stem cell differentiation is a highly dynamic process involving pervasive changes in gene expression. The large majority of existing studies has characterized differentiation at the level of individual molecular profiles, such as the transcriptome or the proteome. To obtain a more comprehensive view, we measured protein, mRNA and microRNA abundance during retinoic acid-driven differentiation of mouse embryonic stem cells. We found that mRNA and protein abundance are typically only weakly correlated across time. To understand this finding, we developed a hierarchical dynamical model that allowed us to integrate all data sets. This model was able to explain mRNA-protein discordance for most genes and identified instances of potential microRNA-mediated regulation. Overexpression or depletion of microRNAs identified by the model, followed by RNA sequencing and protein quantification, were used to follow up on the predictions of the model. Overall, our study shows how multi-omics integration by a dynamical model could be used to nominate candidate regulators.

A swapped genetic code prevents viral infections and gene transfer.

Engineering the genetic code of an organism has been proposed to provide a firewall from natural ecosystems by preventing viral infections and gene transfer1-6. However, numerous viruses and mobile genetic elements encode parts of the translational apparatus7-9, potentially rendering a genetic-code-based firewall ineffective. Here we show that such mobile transfer RNAs (tRNAs) enable gene transfer and allow viral replication in Escherichia coli despite the genome-wide removal of 3 of the 64 codons and the previously essential cognate tRNA and release factor genes. We then establish a genetic firewall by discovering viral tRNAs that provide exceptionally efficient codon reassignment allowing us to develop cells bearing an amino acid-swapped genetic code that reassigns two of the six serine codons to leucine during translation. This amino acid-swapped genetic code renders cells resistant to viral infections by mistranslating viral proteomes and prevents the escape of synthetic genetic information by engineered reliance on serine codons to produce leucine-requiring proteins. As these cells may have a selective advantage over wild organisms due to virus resistance, we also repurpose a third codon to biocontain this virus-resistant host through dependence on an amino acid not found in nature10. Our results may provide the basis for a general strategy to make any organism safely resistant to all natural viruses and prevent genetic information flow into and out of genetically modified organisms.

Systematic conformation-to-phenotype mapping via limited deep-sequencing of proteins.

Non-native conformations drive protein misfolding diseases, complicate bioengineering efforts, and fuel molecular evolution. No current experimental technique is well-suited for elucidating them and their phenotypic effects. Especially intractable are the transient conformations populated by intrinsically disordered proteins. We describe an approach to systematically discover, stabilize, and purify native and non-native conformations, generated in vitro or in vivo, and directly link conformations to molecular, organismal, or evolutionary phenotypes. This approach involves high-throughput disulfide scanning (HTDS) of the entire protein. To reveal which disulfides trap which chromatographically resolvable conformers, we devised a deep-sequencing method for double-Cys variant libraries of proteins that precisely and simultaneously locates both Cys residues within each polypeptide. HTDS of the abundant E. coli periplasmic chaperone HdeA revealed distinct classes of disordered hydrophobic conformers with variable cytotoxicity depending on where the backbone was cross-linked. HTDS can bridge conformational and phenotypic landscapes for many proteins that function in disulfide-permissive environments.

A Proximity biotinylation assay with a host protein bait reveals multiple factors modulating enterovirus replication.

As ultimate parasites, viruses depend on host factors for every step of their life cycle. On the other hand, cells evolved multiple mechanisms of detecting and interfering with viral replication. Yet, our understanding of the complex ensembles of pro- and anti-viral factors is very limited in virtually every virus-cell system. Here we investigated the proteins recruited to the replication organelles of poliovirus, a representative of the genus Enterovirus of the Picornaviridae family. We took advantage of a strict dependence of enterovirus replication on a host protein GBF1, and established a stable cell line expressing a truncated GBF1 fused to APEX2 peroxidase that effectively supported viral replication upon inhibition of the endogenous GBF1. This construct biotinylated multiple host and viral proteins on the replication organelles. Among the viral proteins, the polyprotein cleavage intermediates were overrepresented, suggesting that the GBF1 environment is linked to viral polyprotein processing. The proteomics characterization of biotinylated host proteins identified multiple proteins previously associated with enterovirus replication, as well as more than 200 new factors recruited to the replication organelles. RNA metabolism proteins, many of which normally localize in the nucleus, constituted the largest group, underscoring the massive release of nuclear factors into the cytoplasm of infected cells and their involvement in viral replication. Functional analysis of several newly identified proteins revealed both pro- and anti-viral factors, including a novel component of infection-induced stress granules. Depletion of these proteins similarly affected the replication of diverse enteroviruses indicating broad conservation of the replication mechanisms. Thus, our data significantly expand the knowledge of the composition of enterovirus replication organelles, provide new insights into viral replication, and offer a novel resource for identifying targets for anti-viral interventions.

Quality assurance of hematopoietic stem cells by macrophages determines stem cell clonality.

Tissue-specific stem cells persist for a lifetime and can differentiate to maintain homeostasis or transform to initiate cancer. Despite their importance, there are no described quality assurance mechanisms for newly formed stem cells. We observed intimate and specific interactions between macrophages and nascent blood stem cells in zebrafish embryos. Macrophage interactions frequently led to either removal of cytoplasmic material and stem cell division or complete engulfment and stem cell death. Stressed stem cells were marked by surface Calreticulin, which stimulated macrophage interactions. Using cellular barcoding, we found that Calreticulin knock-down or embryonic macrophage depletion reduced the number of stem cell clones that established adult hematopoiesis. Our work supports a model in which embryonic macrophages determine hematopoietic clonality by monitoring stem cell quality.

Hyaluronic Acid Nanoparticles for Immunogenic Chemotherapy of Leukemia and T-Cell Lymphoma.

Ratiometric delivery of combination chemotherapy can achieve therapeutic efficacy based on synergistic interactions between drugs. It is critical to design such combinations with drugs that complement each other and reduce cancer growth through multiple mechanisms. Using hyaluronic acid (HA) as a carrier, two chemotherapeutic agents-doxorubicin (DOX) and camptothecin (CPT)-were incorporated and tested for their synergistic potency against a broad panel of blood-cancer cell lines. The pair also demonstrated the ability to achieve immunogenic cell death by increasing the surface exposure levels of Calreticulin, thereby highlighting its ability to induce apoptosis via an alternate pathway. Global proteomic profiling of cancer cells treated with HA-DOX-CPT identified pathways that could potentially predict patient sensitivity to HA-DOX-CPT. This lays the foundation for further exploration of integrating drug delivery and proteomics in personalized immunogenic chemotherapy.

Development of Photolenalidomide for Cellular Target Identification.

The thalidomide analogue lenalidomide (Len) is a clinical therapeutic that alters the substrate engagement of cereblon (CRBN), a substrate receptor for the CRL4 E3 ubiquitin ligase. Here, we report the development of photolenalidomide (pLen), a Len probe with a photoaffinity label and enrichment handle, designed for target identification by chemical proteomics. pLen preserves the substrate degradation profile, phenotypic antiproliferative and immunomodulatory properties of Len, and enhances interactions with the thalidomide-binding domain of CRBN, as revealed by binding site mapping and molecular modeling. Using pLen, we captured the known targets IKZF1 and CRBN from multiple myeloma MM.1S cells and further identified a new target, eukaryotic translation initiation factor 3 subunit i (eIF3i), from HEK293T cells. eIF3i is directly labeled by pLen and forms a ternary complex with CRBN in the presence of Len across several epithelial cell lines but is itself not ubiquitylated or degraded. These data point to the existence of a broader array of targets induced by ligands to CRBN that may or may not be degraded, which can be identified by the highly translatable application of pLen to additional biological systems.

In-depth analysis of proteomic and genomic fluctuations during the time course of human embryonic stem cells directed differentiation into beta cells.

Pluripotent stem cells (PSC) endocrine differentiation at a large scale allows sampling of transcriptome and proteome with phosphoproteome (proteoform) at specific time points. We describe the dynamic time course of changes in cells undergoing directed beta-cell differentiation and show target proteins or previously unknown phosphorylation of critical proteins in pancreas development, NKX6-1, and Chromogranin A (CHGA). We describe fluctuations in the correlation between gene expression, protein abundance, and phosphorylation, following differentiation protocol perturbations at all stages to identify proteoform profiles. Our modeling recognizes outliers on a phenomic landscape of endocrine differentiation, and we describe new biological pathways involved. We have validated our proteomic data by analyzing independent single-cell RNAseq datasets for in-vitro pancreatic islet production and corroborated our findings for several proteins suggestive as targets for future research. The single-cell analysis combined with proteoform data places new protein targets within the specific time point and at the specific pancreatic lineage of differentiating stem cells. We suggest that non-correlating proteins abundances or new phosphorylation motifs of NKX6.1 and CHGA point to new signaling pathways that may play an essential role in beta-cell development. We present our findings for the research community's use to improve endocrine differentiation protocols and developmental studies.

Biliary excretion of excess iron in mice requires hepatocyte iron import by Slc39a14.

Iron is essential for erythropoiesis and other biological processes, but is toxic in excess. Dietary absorption of iron is a highly regulated process and is a major determinant of body iron levels. Iron excretion, however, is considered a passive, unregulated process, and the underlying pathways are unknown. Here we investigated the role of metal transporters SLC39A14 and SLC30A10 in biliary iron excretion. While SLC39A14 imports manganese into the liver and other organs under physiological conditions, it imports iron under conditions of iron excess. SLC30A10 exports manganese from hepatocytes into the bile. We hypothesized that biliary excretion of excess iron would be impaired by SLC39A14 and SLC30A10 deficiency. We therefore analyzed biliary iron excretion in Slc39a14-and Slc30a10-deficient mice raised on iron-sufficient and -rich diets. Bile was collected surgically from the mice, then analyzed with nonheme iron assays, mass spectrometry, ELISAs, and an electrophoretic assay for iron-loaded ferritin. Our results support a model in which biliary excretion of excess iron requires iron import into hepatocytes by SLC39A14, followed by iron export into the bile predominantly as ferritin, with iron export occurring independently of SLC30A10. To our knowledge, this is the first report of a molecular determinant of mammalian iron excretion and can serve as basis for future investigations into mechanisms of iron excretion and relevance to iron homeostasis.

Quantitative proteomic analysis of extracellular vesicle subgroups isolated by an optimized method combining polymer-based precipitation and size exclusion chromatography.

The molecular characterization of extracellular vesicles (EVs) has revealed a great heterogeneity in their composition at a cellular and tissue level. Current isolation methods fail to efficiently separate EV subtypes for proteomic and functional analysis. The aim of this study was to develop a reproducible and scalable isolation workflow to increase the yield and purity of EV preparations. Through a combination of polymer-based precipitation and size exclusion chromatography (Pre-SEC), we analyzed two subsets of EVs based on their CD9, CD63 and CD81 content and elution time. EVs were characterized using transmission electron microscopy, nanoparticle tracking analysis, and Western blot assays. To evaluate differences in protein composition between the early- and late-eluting EV fractions, we performed a quantitative proteomic analysis of MDA-MB-468-derived EVs. We identified 286 exclusive proteins in early-eluting fractions and 148 proteins with a differential concentration between early- and late-eluting fractions. A density gradient analysis further revealed EV heterogeneity within each analyzed subgroup. Through a systems biology approach, we found significant interactions among proteins contained in the EVs which suggest the existence of functional clusters related to specific biological processes. The workflow presented here allows the study of EV subtypes within a single cell type and contributes to standardizing the EV isolation for functional studies.