Bacteria-to-Human Protein Networks Reveal Origins of Endogenous DNA Damage.

DNA damage provokes mutations and cancer and results from external carcinogens or endogenous cellular processes. However, the intrinsic instigators of endogenous DNA damage are poorly understood. Here, we identify proteins that promote endogenous DNA damage when overproduced: the DNA "damage-up" proteins (DDPs). We discover a large network of DDPs in Escherichia coli and deconvolute them into six function clusters, demonstrating DDP mechanisms in three: reactive oxygen increase by transmembrane transporters, chromosome loss by replisome binding, and replication stalling by transcription factors. Their 284 human homologs are over-represented among known cancer drivers, and their RNAs in tumors predict heavy mutagenesis and a poor prognosis. Half of the tested human homologs promote DNA damage and mutation when overproduced in human cells, with DNA damage-elevating mechanisms like those in E. coli. Our work identifies networks of DDPs that provoke endogenous DNA damage and may reveal DNA damage-associated functions of many human known and newly implicated cancer-promoting proteins.

Enhancer RNA m6A methylation facilitates transcriptional condensate formation and gene activation.

The mechanistic understanding of nascent RNAs in transcriptional control remains limited. Here, by a high sensitivity method methylation-inscribed nascent transcripts sequencing (MINT-seq), we characterized the landscapes of N6-methyladenosine (m6A) on nascent RNAs. We uncover heavy but selective m6A deposition on nascent RNAs produced by transcription regulatory elements, including promoter upstream antisense RNAs and enhancer RNAs (eRNAs), which positively correlates with their length, inclusion of m6A motif, and RNA abundances. m6A-eRNAs mark highly active enhancers, where they recruit nuclear m6A reader YTHDC1 to phase separate into liquid-like condensates, in a manner dependent on its C terminus intrinsically disordered region and arginine residues. The m6A-eRNA/YTHDC1 condensate co-mixes with and facilitates the formation of BRD4 coactivator condensate. Consequently, YTHDC1 depletion diminished BRD4 condensate and its recruitment to enhancers, resulting in inhibited enhancer and gene activation. We propose that chemical modifications of eRNAs together with reader proteins play broad roles in enhancer activation and gene transcriptional control.

Structural Insights of Transcriptionally Active, Full-Length Androgen Receptor Coactivator Complexes.

Steroid receptors activate gene transcription by recruiting coactivators to initiate transcription of their target genes. For most nuclear receptors, the ligand-dependent activation function domain-2 (AF-2) is a primary contributor to the nuclear receptor (NR) transcriptional activity. In contrast to other steroid receptors, such as ERα, the activation function of androgen receptor (AR) is largely dependent on its ligand-independent AF-1 located in its N-terminal domain (NTD). It remains unclear why AR utilizes a different AF domain from other receptors despite that NRs share similar domain organizations. Here, we present cryoelectron microscopy (cryo-EM) structures of DNA-bound full-length AR and its complex structure with key coactivators, SRC-3 and p300. AR dimerization follows a unique head-to-head and tail-to-tail manner. Unlike ERα, AR directly contacts a single SRC-3 and p300. The AR NTD is the primary site for coactivator recruitment. The structures provide a basis for understanding assembly of the AR:coactivator complex and its domain contributions for coactivator assembly and transcriptional regulation.

Transcriptional coactivation of NRF2 signaling in cardiac fibroblasts promotes resistance to oxidative stress.

We recently discovered that steroid receptor coactivators (SRCs) SRCs-1, 2 and 3, are abundantly expressed in cardiac fibroblasts (CFs) and their activation with the SRC small molecule stimulator MCB-613 improves cardiac function and dramatically lowers pro-fibrotic signaling in CFs post-myocardial infarction. These findings suggest that CF-derived SRC activation could be beneficial in the mitigation of chronic heart failure after ischemic insult. However, the cardioprotective mechanisms by which CFs contribute to cardiac pathological remodeling are unclear. Here we present studies designed to identify the molecular and cellular circuitry that governs the anti-fibrotic effects of an MCB-613 derivative, MCB-613-10-1, in CFs. We performed cytokine profiling and whole transcriptome and proteome analyses of CF-derived signals in response to MCB-613-10-1. We identified the NRF2 pathway as a direct MCB-613-10-1 therapeutic target for promoting resistance to oxidative stress in CFs. We show that MCB-613-10-1 promotes cell survival of anti-fibrotic CFs exposed to oxidative stress by suppressing apoptosis. We demonstrate that an increase in HMOX1 expression contributes to CF resistance to oxidative stress-mediated apoptosis via a mechanism involving SRC co-activation of NRF2, hence reducing inflammation and fibrosis. We provide evidence that MCB-613-10-1 acts as a protectant against oxidative stress-induced mitochondrial damage. Our data reveal that SRC stimulation of the NRF2 transcriptional network promotes resistance to oxidative stress and highlights a mechanistic approach toward addressing pathologic cardiac remodeling.

Incidence of and Factors Associated With Recurrent Firearm Injury Among Patients Presenting to St. Louis Trauma Centers, 2010 to 2019 : A Cohort Study.

BACKGROUND: Firearm injuries are a public health crisis in the United States. OBJECTIVE: To examine the incidence and factors associated with recurrent firearm injuries and death among patients presenting with an acute (index), nonfatal firearm injury. DESIGN: Multicenter, observational, cohort study. SETTING: Four adult and pediatric level I trauma hospitals in St. Louis, Missouri, 2010 to 2019. PARTICIPANTS: Consecutive adult and pediatric patients (n = 9553) presenting to a participating hospital with a nonfatal acute firearm injury. MEASUREMENTS: Data on firearm-injured patient demographics, hospital and diagnostic information, health insurance status, and death were collected from the St. Louis Region-Wide Hospital-Based Violence Intervention Program Data Repository. The Centers for Disease Control and Prevention (CDC) Social Vulnerability Index was used to characterize the social vulnerability of the census tracts of patients' residences. Analysis included descriptive statistics and time-to-event analyses estimating the probability of experiencing a recurrent firearm injury. RESULTS: We identified 10 293 acutely firearm-injured patients of whom 9553 survived the injury and comprised the analytic sample. Over a median follow-up of 3.5 years (IQR, 1.5 to 6.4 years), 1155 patients experienced a recurrent firearm injury including 5 firearm suicides and 149 fatal firearm injuries. Persons experiencing recurrent firearm injury were young (25.3 ± 9.5 years), predominantly male (93%), Black (96%), and uninsured (50%), and resided in high social vulnerability regions (65%). The estimated risk for firearm reinjury was 7% at 1 year and 17% at 8 years. LIMITATIONS: Limited data on comorbidities and patient-level social determinants of health. Inability to account for recurrent injuries presenting to nonstudy hospitals. CONCLUSION: Recurrent injury and death are frequent among survivors of firearm injury, particularly among patients from socially vulnerable areas. Our findings highlight the need for interventions to prevent recurrence. PRIMARY FUNDING SOURCE: Emergency Medicine Foundation-AFFIRM and Missouri Foundation for Health.

Mutual regulation of tumour vessel normalization and immunostimulatory reprogramming.

Blockade of angiogenesis can retard tumour growth, but may also paradoxically increase metastasis. This paradox may be resolved by vessel normalization, which involves increased pericyte coverage, improved tumour vessel perfusion, reduced vascular permeability, and consequently mitigated hypoxia. Although these processes alter tumour progression, their regulation is poorly understood. Here we show that type 1 T helper (TH1) cells play a crucial role in vessel normalization. Bioinformatic analyses revealed that gene expression features related to vessel normalization correlate with immunostimulatory pathways, especially T lymphocyte infiltration or activity. To delineate the causal relationship, we used various mouse models with vessel normalization or T lymphocyte deficiencies. Although disruption of vessel normalization reduced T lymphocyte infiltration as expected, reciprocal depletion or inactivation of CD4+ T lymphocytes decreased vessel normalization, indicating a mutually regulatory loop. In addition, activation of CD4+ T lymphocytes by immune checkpoint blockade increased vessel normalization. TH1 cells that secrete interferon-γ are a major population of cells associated with vessel normalization. Patient-derived xenograft tumours growing in immunodeficient mice exhibited enhanced hypoxia compared to the original tumours in immunocompetent humans, and hypoxia was reduced by adoptive TH1 transfer. Our findings elucidate an unexpected role of TH1 cells in vasculature and immune reprogramming. TH1 cells may be a marker and a determinant of both immune checkpoint blockade and anti-angiogenesis efficacy.

Machine Learning Methods for Endocrine Disrupting Potential Identification Based on Single-Cell Data.

Humans are continuously exposed to a variety of toxicants and chemicals which is exacerbated during and after environmental catastrophes such as floods, earthquakes, and hurricanes. The hazardous chemical mixtures generated during these events threaten the health and safety of humans and other living organisms. This necessitates the development of rapid decision-making tools to facilitate mitigating the adverse effects of exposure on the key modulators of the endocrine system, such as the estrogen receptor alpha (ERα), for example. The mechanistic stages of the estrogenic transcriptional activity can be measured with high content/high throughput microscopy-based biosensor assays at the single-cell level, which generates millions of object-based minable data points. By combining computational modeling and experimental analysis, we built a highly accurate data-driven classification framework to assess the endocrine disrupting potential of environmental compounds. The effects of these compounds on the ERα pathway are predicted as being receptor agonists or antagonists using the principal component analysis (PCA) projections of high throughput, high content image analysis descriptors. The framework also combines rigorous preprocessing steps and nonlinear machine learning algorithms, such as the Support Vector Machines and Random Forest classifiers, to develop highly accurate mathematical representations of the separation between ERα agonists and antagonists. The results show that Support Vector Machines classify the unseen chemicals correctly with more than 96% accuracy using the proposed framework, where the preprocessing and the PCA steps play a key role in suppressing experimental noise and unraveling hidden patterns in the dataset.

Implementing a hospital-based violence intervention program for assault-injured youth: implications for social work practice.

Youth in the U.S. experience a high rate of assault-related injuries resulting in physical, psychological and social sequelae that require a wide range of services after discharge from the hospital. Hospital-based violence intervention programs (HVIP's) have been developed to engage youth in services designed to reduce the incidence of violent injury in young people. HVIP's combine the efforts of medical staff with community-based partners to provide trauma-informed care to violently-injured people and have been found to be a cost-effective means to reduce re-injury rates and improve social and behavioral health outcomes. Few studies have explored the organizational and community level factors that impact implementation of these important and complex interventions. The objective of this study was to develop an in-depth understanding of the factors that impact HVIP implementation from the perspectives of 41 stakeholders through qualitative interviews. Thematic analysis generated three themes that included the importance of integrated, collaborative care, the need for providers who can perform multiple service roles and deploy a range of skills, and the importance of engaging clients through extended contact. In this article we explore these themes and their implications for healthcare social work.

Validation Studies for Single Circulating Trophoblast Genetic Testing as a Form of Noninvasive Prenatal Diagnosis.

It has long been appreciated that genetic analysis of fetal or trophoblast cells in maternal blood could revolutionize prenatal diagnosis. We implemented a protocol for single circulating trophoblast (SCT) testing using positive selection by magnetic-activated cell sorting and single-cell low-coverage whole-genome sequencing to detect fetal aneuploidies and copy-number variants (CNVs) at ∼1 Mb resolution. In 95 validation cases, we identified on average 0.20 putative trophoblasts/mL, of which 55% were of high quality and scorable for both aneuploidy and CNVs. We emphasize the importance of analyzing individual cells because some cells are apoptotic, in S-phase, or otherwise of poor quality. When two or more high-quality trophoblast cells were available for singleton pregnancies, there was complete concordance between all trophoblasts unless there was evidence of confined placental mosaicism. SCT results were highly concordant with available clinical data from chorionic villus sampling (CVS) or amniocentesis procedures. Although determining the exact sensitivity and specificity will require more data, this study further supports the potential for SCT testing to become a diagnostic prenatal test.

Estrogen-induced transcription at individual alleles is independent of receptor level and active conformation but can be modulated by coactivators activity.

Steroid hormones are pivotal modulators of pathophysiological processes in many organs, where they interact with nuclear receptors to regulate gene transcription. However, our understanding of hormone action at the single cell level remains incomplete. Here, we focused on estrogen stimulation of the well-characterized GREB1 and MYC target genes that revealed large differences in cell-by-cell responses, and, more interestingly, between alleles within the same cell, both over time and hormone concentration. We specifically analyzed the role of receptor level and activity state during allele-by-allele regulation and found that neither receptor level nor activation status are the determinant of maximal hormonal response, indicating that additional pathways are potentially in place to modulate cell- and allele-specific responses. Interestingly, we found that a small molecule inhibitor of the arginine methyltransferases CARM1 and PRMT6 was able to increase, in a gene specific manner, the number of active alleles/cell before and after hormonal stimulation, suggesting that mechanisms do indeed exist to modulate hormone receptor responses at the single cell and allele level.

The SINEB1 element in the long non-coding RNA Malat1 is necessary for TDP-43 proteostasis.

Transposable elements (TEs) comprise a large proportion of long non-coding RNAs (lncRNAs). Here, we employed CRISPR to delete a short interspersed nuclear element (SINE) in Malat1, a cancer-associated lncRNA, to investigate its significance in cellular physiology. We show that Malat1 with a SINE deletion forms diffuse nuclear speckles and is frequently translocated to the cytoplasm. SINE-deleted cells exhibit an activated unfolded protein response and PKR and markedly increased DNA damage and apoptosis caused by dysregulation of TDP-43 localization and formation of cytotoxic inclusions. TDP-43 binds stronger to Malat1 without the SINE and is likely 'hijacked' by cytoplasmic Malat1 to the cytoplasm, resulting in the depletion of nuclear TDP-43 and redistribution of TDP-43 binding to repetitive element transcripts and mRNAs encoding mitotic and nuclear-cytoplasmic regulators. The SINE promotes Malat1 nuclear retention by facilitating Malat1 binding to HNRNPK, a protein that drives RNA nuclear retention, potentially through direct interactions of the SINE with KHDRBS1 and TRA2A, which bind to HNRNPK. Losing these RNA-protein interactions due to the SINE deletion likely creates more available TDP-43 binding sites on Malat1 and subsequent TDP-43 aggregation. These results highlight the significance of lncRNA TEs in TDP-43 proteostasis with potential implications in both cancer and neurodegenerative diseases.

Prevalence and correlates of antisocial personality disorder in older adults.

OBJECTIVES: There is a paucity of research on antisocial personality disorder (ASPD) in the geriatric population and the majority of knowledge on the disorder is drawn from young adult samples. Researchers posit that the prevalence of ASPD as well as other personality disorders (PDs) is underestimated among older adults. Using a nationally representative sample, the present study examines the prevalence and correlates of ASPD in adults ages 50 and older. METHODS: We analyzed data from the National Epidemiologic Survey on Alcohol and Related Conditions Waves I and III. Multivariate logistic regression analyses were employed to investigate associations between ASPD and sociodemographic characteristics. A series of logistic regression analyses were also conducted to study associations between ASPD and medical conditions (liver and cardiovascular disease, arthritis, and stomach ulcer), major psychiatric disorders (lifetime major depressive disorder, mania, and generalized anxiety disorder), and substance use disorders (lifetime alcohol, marijuana, cocaine, heroin, and nicotine use disorders). RESULTS: Findings indicated that the prevalence of ASPD increases through early adulthood, with a peak at 3.91% in younger adults and decline to 0.78% in adults ages ≥65. Older adults with ASPD are more likely to be diagnosed with a substance use disorder, major depression, mania, and generalized anxiety disorder as well as each medical condition. CONCLUSION: Older adults with ASPD experience increased rates of medical and psychiatric comorbidities. These conditions exacerbate the existing challenges associated with diagnosing and treating this population and may have serious consequences for the patient, their caregivers and society.

Classification of estrogenic compounds by coupling high content analysis and machine learning algorithms.

Environmental toxicants affect human health in various ways. Of the thousands of chemicals present in the environment, those with adverse effects on the endocrine system are referred to as endocrine-disrupting chemicals (EDCs). Here, we focused on a subclass of EDCs that impacts the estrogen receptor (ER), a pivotal transcriptional regulator in health and disease. Estrogenic activity of compounds can be measured by many in vitro or cell-based high throughput assays that record various endpoints from large pools of cells, and increasingly at the single-cell level. To simultaneously capture multiple mechanistic ER endpoints in individual cells that are affected by EDCs, we previously developed a sensitive high throughput/high content imaging assay that is based upon a stable cell line harboring a visible multicopy ER responsive transcription unit and expressing a green fluorescent protein (GFP) fusion of ER. High content analysis generates voluminous multiplex data comprised of minable features that describe numerous mechanistic endpoints. In this study, we present a machine learning pipeline for rapid, accurate, and sensitive assessment of the endocrine-disrupting potential of benchmark chemicals based on data generated from high content analysis. The multidimensional imaging data was used to train a classification model to ultimately predict the impact of unknown compounds on the ER, either as agonists or antagonists. To this end, both linear logistic regression and nonlinear Random Forest classifiers were benchmarked and evaluated for predicting the estrogenic activity of unknown compounds. Furthermore, through feature selection, data visualization, and model discrimination, the most informative features were identified for the classification of ER agonists/antagonists. The results of this data-driven study showed that highly accurate and generalized classification models with a minimum number of features can be constructed without loss of generality, where these machine learning models serve as a means for rapid mechanistic/phenotypic evaluation of the estrogenic potential of many chemicals.

Bexarotene - a novel modulator of AURKA and the primary cilium in VHL-deficient cells.

Loss of the gene von Hippel-Lindau (VHL) is associated with loss of primary cilia and is causally linked to elevated levels of Aurora kinase A (AURKA). We developed an image-based high-throughput screening (HTS) assay using a dual-labeling image analysis strategy that identifies both the cilium and the basal body. By using this strategy, we screened small-molecule compounds for the targeted rescue of cilia defects associated with VHL deficiency with high accuracy and reproducibility. Bexarotene was identified and validated as a positive regulator of the primary cilium. Importantly, the inability of an alternative retinoid X receptor (RXR) agonist to rescue ciliogenesis, in contrast to bexarotene, suggested that multiple bexarotene-driven mechanisms were responsible for the rescue. We found that bexarotene decreased AURKA expression in VHL-deficient cells, thereby restoring the ability of these cells to ciliate in the absence of VHL Finally, bexarotene treatment reduced the propensity of subcutaneous lesions to develop into tumors in a mouse xenograft model of renal cell carcinoma (RCC), with a concomitant decrease in activated AURKA, highlighting the potential of bexarotene treatment as an intervention strategy in the clinic to manage renal cystogenesis associated with VHL deficiency and elevated AURKA expression.

Measuring Mobility in Chromatin by Intensity-Sorted FCS.

The architectural organization of chromatin can play an important role in genome regulation by affecting the mobility of molecules within its surroundings via binding interactions and molecular crowding. The diffusion of molecules at specific locations in the nucleus can be studied by fluorescence correlation spectroscopy (FCS), a well-established technique based on the analysis of fluorescence intensity fluctuations detected in a confocal observation volume. However, detecting subtle variations of mobility between different chromatin regions remains challenging with currently available FCS methods. Here, we introduce a method that samples multiple positions by slowly scanning the FCS observation volume across the nucleus. Analyzing the data in short time segments, we preserve the high temporal resolution of single-point FCS while probing different nuclear regions in the same cell. Using the intensity level of the probe (or a DNA marker) as a reference, we efficiently sort the FCS segments into different populations and obtain average correlation functions that are associated to different chromatin regions. This sorting and averaging strategy renders the method statistically robust while preserving the observation of intranuclear variations of mobility. Using this approach, we quantified diffusion of monomeric GFP in high versus low chromatin density regions. We found that GFP mobility was reduced in heterochromatin, especially within perinucleolar heterochromatin. Moreover, we found that modulation of chromatin compaction by ATP depletion, or treatment with solutions of different osmolarity, differentially affected the ratio of diffusion in both regions. Then, we used the approach to probe the mobility of estrogen receptor-α in the vicinity of an integrated multicopy prolactin gene array. Finally, we discussed the coupling of this method with stimulated emission depletion FCS for performing FCS at subdiffraction spatial scales.

Strategic Storytelling: An Exploration of the Professional Practices of Mental Health Peer Providers.

Peer providers of mental health services use their personal illness and recovery narratives to help other mental health service users. Despite a substantial body of evidence supporting the effectiveness of these providers, little is known about the underlying strategies they employ in their professional practice. In this study, I used in-depth interviews with 23 peers to explore the most important practices they used in their day-to-day work with others. Results indicated that peers engaged in a reflexive process to strategically use their personal illness and recovery stories to help others re-story their life narratives. Peers also used communication strategies from motivational and cognitive-behavioral treatment approaches to engage, inspire, and mentor other service users. Findings suggest the need for research that further explores the rhetorical strategies used by peers using narrative methods. The development and testing of professional development opportunities to assist peers in maximizing their therapeutic potential are also warranted.

SRC-3Delta4 mediates the interaction of EGFR with FAK to promote cell migration.

EGF induces signal transduction between EGFR and FAK, and FAK is required for EGF-induced cell migration. It is unknown, however, what factor mediates the interaction between EGFR and FAK and leads to EGF-induced FAK phosphorylation. Here, we identify SRC-3Delta4, a splicing isoform of the SRC-3 oncogene, as a signaling adaptor that links EGFR and FAK and promotes EGF-induced phosphorylations of FAK and c-Src. We identify three PAK1-mediated phosphorylations in SRC-3Delta4 that promote the localization of SRC-3Delta4 to the plasma membrane and mediate the interactions with EGFR and FAK. Importantly, overexpression of SRC-3Delta4 promotes MDA-MB231-induced breast tumor metastasis. Our findings identify phosphorylated SRC-3Delta4 as a missing adaptor between EGFR and its downstream signaling molecule FAK to coordinately regulate EGF-induced cell migration. Our study also reveals that a nuclear receptor coactivator can act in the periphery of a cell to directly mediate activation of an enzyme.

An Exploration of Factors that Effect the Implementation of Peer Support Services in Community Mental Health Settings.

This study explored the integration of peer services into community mental health settings through qualitative interviews with peer-providers and non-peer mental health workers. Results show peer job satisfaction was contingent upon role clarity, autonomy, and acceptance by non-peer coworkers. Mental health workers reported the need for organizational support for peer services and guidance about how to utilize peers, negotiate their professional boundaries and accommodate their mental health needs. Effective peer integration requires organizational readiness, staff preparation and clear policies and procedures. Consultation from consumer-based organizations, enhanced professional competencies, and professional development and career advancement opportunities for peers represent important resources.

High-Content Screening Identifies Src Family Kinases as Potential Regulators of AR-V7 Expression and Androgen-Independent Cell Growth.

BACKGROUND: AR-V7 is an androgen receptor (AR) splice variant that lacks the ligand-binding domain and is isolated from prostate cancer cell lines. Increased expression of AR-V7 is associated with the transition from hormone-sensitive prostate cancer to more advanced castration-resistant prostate cancer (CRPC). Due to the loss of the ligand-binding domain, AR-V7 is not responsive to traditional AR-targeted therapies, and the mechanisms that regulate AR-V7 are still incompletely understood. Therefore, we aimed to explore existing classes of small molecules that may regulate AR-V7 expression and intracellular localization and their potential therapeutic role in CRPC. METHODS: We used AR high-content analysis (AR-HCA) to characterize the effects of a focused library of well-characterized clinical compounds on AR-V7 expression at the single-cell level in PC3 prostate cancer cells stably expressing green fluorescent protein (GFP)-AR-V7 (GFP-AR-V7:PC3). In parallel, an orthogonal AR-HCA screen of a small interfering (si)RNA library targeting 635 protein kinases was performed in GFP-AR-V7:PC3. The effect of the Src-Abl inhibitor PD 180970 was further characterized using cell-proliferation assays, quantitative PCR, and western blot analysis in multiple hormone-sensitive and CRPC cell lines. RESULTS: Compounds that tended to target Akt, Abl, and Src family kinases (SFKs) decreased overall AR-V7 expression, nuclear translocation, absolute nuclear level, and/or altered nuclear distribution. We identified 20 protein kinases that, when knocked down, either decreased nuclear GFP-AR-V7 levels or altered AR-V7 nuclear distribution, a set that included the SFKs Src and Fyn. The Src-Abl dual kinase inhibitor PD180970 decreased expression of AR-V7 by greater than 46% and decreased ligand-independent transcription of AR target genes in the 22RV1 human prostate carcinoma cell line. Further, PD180970 inhibited androgen-independent cell proliferation in endogenous-AR-V7-expressing prostate cancer cell lines and also overcame bicalutamide resistance observed in the 22RV1 cell line. CONCLUSIONS: SFKs, especially Src and Fyn, may be important upstream regulators of AR-V7 expression and represent promising targets in a subset of CRPCs expressing high levels of AR-V7. Prostate 77:82-93, 2017. © 2016 Wiley Periodicals, Inc.

Use of HCA in subproteome-immunization and screening of hybridoma supernatants to define distinct antibody binding patterns.

Understanding the properties and functions of complex biological systems depends upon knowing the proteins present and the interactions between them. Recent advances in mass spectrometry have given us greater insights into the participating proteomes, however, monoclonal antibodies remain key to understanding the structures, functions, locations and macromolecular interactions of the involved proteins. The traditional single immunogen method to produce monoclonal antibodies using hybridoma technology are time, resource and cost intensive, limiting the number of reagents that are available. Using a high content analysis screening approach, we have developed a method in which a complex mixture of proteins (e.g., subproteome) is used to generate a panel of monoclonal antibodies specific to a subproteome located in a defined subcellular compartment such as the nucleus. The immunofluorescent images in the primary hybridoma screen are analyzed using an automated processing approach and classified using a recursive partitioning forest classification model derived from images obtained from the Human Protein Atlas. Using an ammonium sulfate purified nuclear matrix fraction as an example of reverse proteomics, we identified 866 hybridoma supernatants with a positive immunofluorescent signal. Of those, 402 produced a nuclear signal from which patterns similar to known nuclear matrix associated proteins were identified. Detailed here is our method, the analysis techniques, and a discussion of the application to further in vivo antibody production.