Intrarenal pressure and flow rate profile using LithoVue™ elite: impact of different irrigation systems and working channel instruments.

PURPOSE: To report real-time IRP and FR while performing flexible ureteroscopy in porcine kidney model utilizing LithoVue™ Elite (Boston Scientific®) with different irrigation systems, including automated pumps. METHODS: Using an ex-vivo model of porcine kidney, IRPs were measured with LithoVue Elite. Ureteroscopic settings (US) were tested with all permutations of irrigation methods (IM), working channel occupant (WCO), and ureteral access sheaths (UAS). IMs included: Single Action Pumping System (SAPS™, Boston Scientific), Thermedx FluidSmart™ (Stryker®), and ENDOMAT™ (Karl Storz®). Pumps were tested at 50, 100, and 150 mmHg. WCOs included a 1.9Fr zero-tip basket, 200 µm, and 365 µm laser fibers. UASs utilized 11/13Fr and 12/14Fr 36 cm. RESULTS: 84 different US were tested (252 experiments). ENDOMAT had higher IRP but the same FR as Thermedx at the same US for 50 and 100 mmHg (p < 0.01). SAPS had higher IRP and FR than pumps in all US studies (p < 0.01). There was positive correlation between pressure set by the pump and both IRP and FR (rho > 0.9). As the diameter of the WCO increased, lower IRP and FR were observed with the pumps (p < 0.01). With SAPS, IRP was similar regardless of WCO, but FR was decreased with the increased diameter of WCO (p = 0.81 and p < 0.01, respectively). There was significantly higher IRP when using 11/13Fr UAS than 12/14Fr (p < 0.01). CONCLUSION: IRP was higher with SAPS than automated pumps. ENDOMAT showed higher IRP than Thermedx when under 150 mmHg. IRP and FR increase with higher pump pressure and decrease with larger diameter WCO. Likewise, a larger UAS significantly reduced IRP.

Open or robotic? Radical cystectomies for patients with non-metastatic bladder cancer: A systematic review and meta-analysis.

Background: This systematic review and meta-analysis will review randomized control trials for localized bladder cancer, evaluating surgical and pathologic outcomes of ORC versus RARC. Methods: Randomized studies evaluating adults with non-metastatic bladder cancer who underwent a radical cystectomy. Randomized trials were selected for final review. Data was extracted and analyzed with Revman 5 software. The primary outcome was complication rates within 90 days. Secondary outcomes included postoperative quality of life, estimated intraoperative blood loss, and other perioperative outcomes. Continuous variables were reported using mean difference with 95% confidence intervals, and dichotomous variables were reported using risk difference with 95% confidence intervals with RARC as the experimental group and ORC as the reference group. Results: Of 134 articles screened, six unique randomized studies were selected. For Grade I-II complications, the risk ratio (RR) was 0.92 (95% CI [0.79,1.08], p = 0.33), and for Grade III-V complications, RR 0.93 (95% CI [0.73,1.18], p = 0.59). RARC resulted in decreased blood loss (95% CI [-438.08, -158.44], p < 0.00001) and longer operative time (95% CI [55.23, 133.13], p < 0.00001). Quality of life using the EORTC-QLQ-30 global health score at 3 months post-op appeared to favor RARC with a mean difference of 4.46 points (95% CI [1.78, 7.15], p = 0.001). Pathologic outcomes neither statistically nor clinically favored one modality, as there was no significant difference between mean lymph node yield (p = 0.49), positive lymph nodes (p = 1.00), and positive surgical margins (p = 0.85) between the surgical modalities. Conclusions: Although one surgical modality is not overtly superior, the choice may be decided by mitigating individual operative risk factors like intraoperative blood loss, operative time, post-operative quality of life, as well as institutional costs and learning curve among surgeons.

Preoperative urine culture with contaminants is not associated with increased risk for urinary tract infection after ureteroscopic stone treatment.

PURPOSE: We aimed to assess whether the presence of contaminants in the pre-operative urine culture (preop-UC) predicts postoperative urinary tract infection (postop-UTI) in patients undergoing elective ureteroscopy with laser lithotripsy. METHODS: A retrospective chart review was performed from 01/2019 to 12/2021 examining patients with unilateral stone burden ≤ 2 cm who underwent ureteroscopy with laser lithotripsy and had a preop-UC within 3 months. Positive, negative, contaminated, and polymicrobial definitions for UCs were established in accordance with current guidelines. Patients with positive and polymicrobial cultures were excluded. Postop-UTI was defined as the presence of urinary symptoms and a positive UC within 30 days of the procedure. Multivariable logistic regression models were utilized to evaluate risk factors for contamination in the preop-UC and the risk of postop-UTI. RESULTS: A total of 201 patients met the inclusion-exclusion criteria. Preop-UC was negative in 153 patients and contaminated in 48 patients. Significant contaminant-related factors included female gender and increased BMI. Postop-UTI was diagnosed in 3.2% of patients with negative preop-UCs and 4.2% of patients with contaminants, with no difference between groups (p = 0.67). The regression model determined that the presence of contaminants in preop-UC failed to predict postop-UTI (OR 0.69, p = 0.64). CONCLUSION: The presence of contaminants in preop-UCs is not associated with an increased risk of postop-UTIs after ureteroscopy. Our study supports that contaminants in the preop-UC can be interpreted as a negative UC in terms of postop-UTI risk stratification. Preoperative antibiotics should not be prescribed for patients undergoing uncomplicated ureteroscopy for stone surgery in the setting of a contaminated preop-UC.

Differences in Leukocyte Transcriptomes of Morbidly Obese Patients With High Output Heart Failure: A Pilot Study.

Background and Objectives: Heart failure is characterized by alterations of gene expression that provide insight into the underlying pathophysiologic mechanisms. However, obesity-related high output heart failure (HOHF) is a specific phenotype of heart failure that has not been studied using gene expression. Our aim in this study was to examine the variances in leukocyte transcriptomes of morbidly obese patients with HOHF. Methods: In this cross-sectional study, we applied stranded total RNA-sequencing to six patients with morbid obesity and HOHF and 6 patients with morbid obesity and non-HOHF. Differential gene expression was calculated, and Ingenuity Pathway Analysis software was used to interpret the canonical pathways, functional changes, upstream regulators, and networks in these patients. Results: We found in patients with HOHF that there were 116 differentially expressed genes with upregulation of 114 genes and downregulation of 2 genes. The differentially expressed genes were involved with cell proliferation, mitochondrial function, erythropoiesis, erythrocyte stability, and apoptosis. The top upregulated canonical pathways associated with differentially expressed genes were autophagy, adenosine monophosphate-activated protein kinase signaling, and senescence pathways. We identified GATA binding protein 1 as an upstream regulator and nuclear factor kappa-light-chain-enhancer of activated B cells associated network. Conclusions: We are the first to report the differential gene expression in patients with obesity-related HOHF and reveal the various pathophysiologic mechanisms underlying the disease. Further research is needed to determine the role of cellular function and maintenance, inflammation, and iron homeostasis in obesity-related HOHF.

The antiproliferative effect of FGF2 in K-Ras-driven tumor cells involves modulation of rRNA and the nucleolus.

The nucleolus is sensitive to stress and can orchestrate a chain of cellular events in response to stress signals. Despite being a growth factor, FGF2 has antiproliferative and tumor-suppressive functions in some cellular contexts. In this work, we investigated how the antiproliferative effect of FGF2 modulates chromatin-, nucleolus- and rDNA-associated proteins. The chromatin and nucleolar proteome indicated that FGF2 stimulation modulates proteins related to transcription, rRNA expression and chromatin-remodeling proteins. The global transcriptional rate and nucleolus area increased along with nucleolar disorganization upon 24 h of FGF2 stimulation. FGF2 stimulation induced immature rRNA accumulation by increasing rRNA transcription. The rDNA-associated protein analysis reinforced that FGF2 stimulus interferes with transcription and rRNA processing. RNA Pol I inhibition partially reversed the growth arrest induced by FGF2, indicating that changes in rRNA expression might be crucial for triggering the antiproliferative effect. Taken together, we demonstrate that the antiproliferative FGF2 stimulus triggers significant transcriptional changes and modulates the main cell transcription site, the nucleolus.

Understanding the need for digital twins' data in patient advocacy and forecasting oncology.

Digital twins are made of a real-world component where data is measured and a virtual component where those measurements are used to parameterize computational models. There is growing interest in applying digital twins-based approaches to optimize personalized treatment plans and improve health outcomes. The integration of artificial intelligence is critical in this process, as it enables the development of sophisticated disease models that can accurately predict patient response to therapeutic interventions. There is a unique and equally important application of AI to the real-world component of a digital twin when it is applied to medical interventions. The patient can only be treated once, and therefore, we must turn to the experience and outcomes of previously treated patients for validation and optimization of the computational predictions. The physical component of a digital twins instead must utilize a compilation of available data from previously treated cancer patients whose characteristics (genetics, tumor type, lifestyle, etc.) closely parallel those of a newly diagnosed cancer patient for the purpose of predicting outcomes, stratifying treatment options, predicting responses to treatment and/or adverse events. These tasks include the development of robust data collection methods, ensuring data availability, creating precise and dependable models, and establishing ethical guidelines for the use and sharing of data. To successfully implement digital twin technology in clinical care, it is crucial to gather data that accurately reflects the variety of diseases and the diversity of the population.

Lineage specific extracellular vesicle-associated protein biomarkers for the early detection of high grade serous ovarian cancer.

High grade serous ovarian carcinoma (HGSOC) accounts for ~ 70% of ovarian cancer cases. Non-invasive, highly specific blood-based tests for pre-symptomatic screening in women are crucial to reducing the mortality associated with this disease. Since most HGSOCs typically arise from the fallopian tubes (FT), our biomarker search focused on proteins found on the surface of extracellular vesicles (EVs) released by both FT and HGSOC tissue explants and representative cell lines. Using mass spectrometry, 985 EV proteins (exo-proteins) were identified that comprised the FT/HGSOC EV core proteome. Transmembrane exo-proteins were prioritized because these could serve as antigens for capture and/or detection. With a nano-engineered microfluidic platform, six newly discovered exo-proteins (ACSL4, IGSF8, ITGA2, ITGA5, ITGB3, MYOF) plus a known HGSOC associated protein, FOLR1 exhibited classification performance ranging from 85 to 98% in a case-control study using plasma samples representative of early (including stage IA/B) and late stage (stage III) HGSOCs. Furthermore, by a linear combination of IGSF8 and ITGA5 based on logistic regression analysis, we achieved a sensitivity of 80% with 99.8% specificity and a positive predictive value of 13.8%. Importantly, these exo-proteins also can accurately discriminate between ovarian and 12 types of cancers commonly diagnosed in women. Our studies demonstrate that these lineage-associated exo-biomarkers can detect ovarian cancer with high specificity and sensitivity early and potentially while localized to the FT when patient outcomes are more favorable.

Identification of small extracellular vesicle protein biomarkers for pediatric Ewing Sarcoma.

Ewing Sarcoma (EWS) is the second most common osseous malignancy in children and young adults after osteosarcoma, while it is the fifth common osseous malignancy within adult age population. The clinical presentation of EWS is quite often non-specific, with the most common symptoms at presentation consisting of pain, swelling or general discomfort. The dearth of clinically relevant diagnostic or predictive biomarkers continues to remain a pressing clinical challenge. Identification of tumor specific biomarkers can lend towards an early diagnosis, expedited initiation of therapy, monitoring of therapeutic response, and early detection of recurrence of disease. We carried-out a complex analysis of cell lines and cell line derived small extracellular vesicles (sEVs) using label-free-based Quantitative Proteomic Profiling with an intent to determine shared and distinct features of these tumor cells and their respective sEVs. We analyzed EWS cells with different EWS-ETS fusions (EWS-FLI1 type I, II, and III and EWS-ERG) and their corresponding sEVs. Non-EWS controls included osteosarcoma, rhabdomyosarcoma, and benign cells, i.e., osteoid osteoma and mesenchymal stem cells. Proteomic profiling identified new shared markers between cells and their corresponding cell-derived sEVs and markers which were exclusively enriched in EWS-derived sEVs. These exo-biomarkers identified were validated by in silico approaches of publicly available protein databases and by capillary electrophoresis based western analysis (Wes). Here, we identified a protein biomarker named UGT3A2 and found its expression highly specific to EWS cells and their sEVs compared to control samples. Clinical validation of UGT3A2 expression in patient tumor tissues and plasma derived sEV samples demonstrated its specificity to EWS, indicating its potential as a EWS biomarker.

Proteomic Profiling of Fallopian Tube-Derived Extracellular Vesicles Using a Microfluidic Tissue-on-Chip System.

The human fallopian tube epithelium (hFTE) is the site of fertilization, early embryo development, and the origin of most high-grade serous ovarian cancers (HGSOCs). Little is known about the content and functions of hFTE-derived small extracellular vesicles (sEVs) due to the limitations of biomaterials and proper culture methods. We have established a microfluidic platform to culture hFTE for EV collection with adequate yield for mass spectrometry-based proteomic profiling, and reported 295 common hFTE sEV proteins for the first time. These proteins are associated with exocytosis, neutrophil degranulation, and wound healing, and some are crucial for fertilization processes. In addition, by correlating sEV protein profiles with hFTE tissue transcripts characterized using GeoMx® Cancer Transcriptome Atlas, spatial transcriptomics analysis revealed cell-type-specific transcripts of hFTE that encode sEVs proteins, among which, FLNA, TUBB, JUP, and FLNC were differentially expressed in secretory cells, the precursor cells for HGSOC. Our study provides insights into the establishment of the baseline proteomic profile of sEVs derived from hFTE tissue, and its correlation with hFTE lineage-specific transcripts, which can be used to evaluate whether the fallopian tube shifts its sEV cargo during ovarian cancer carcinogenesis and the role of sEV proteins in fallopian tube reproductive functions.

Dynamic regulation and requirement for ribosomal RNA transcription during mammalian development.

Ribosomal RNA (rRNA) transcription by RNA polymerase I (Pol I) is a critical rate-limiting step in ribosome biogenesis, which is essential for cell survival. Despite its global function, disruptions in ribosome biogenesis cause tissue-specific birth defects called ribosomopathies, which frequently affect craniofacial development. Here, we describe a cellular and molecular mechanism underlying the susceptibility of craniofacial development to disruptions in Pol I transcription. We show that Pol I subunits are highly expressed in the neuroepithelium and neural crest cells (NCCs), which generate most of the craniofacial skeleton. High expression of Pol I subunits sustains elevated rRNA transcription in NCC progenitors, which supports their high tissue-specific levels of protein translation, but also makes NCCs particularly sensitive to rRNA synthesis defects. Consistent with this model, NCC-specific deletion of Pol I subunits Polr1a, Polr1c, and associated factor Tcof1 in mice cell-autonomously diminishes rRNA synthesis, which leads to p53 protein accumulation, resulting in NCC apoptosis and craniofacial anomalies. Furthermore, compound mutations in Pol I subunits and associated factors specifically exacerbate the craniofacial anomalies characteristic of the ribosomopathies Treacher Collins syndrome and Acrofacial Dysostosis-Cincinnati type. Mechanistically, we demonstrate that diminished rRNA synthesis causes an imbalance between rRNA and ribosomal proteins. This leads to increased binding of ribosomal proteins Rpl5 and Rpl11 to Mdm2 and concomitantly diminished binding between Mdm2 and p53. Altogether, our results demonstrate a dynamic spatiotemporal requirement for rRNA transcription during mammalian cranial NCC development and corresponding tissue-specific threshold sensitivities to disruptions in rRNA transcription in the pathogenesis of congenital craniofacial disorders.

Synergistic anti-proliferative activity of JQ1 and GSK2801 in triple-negative breast cancer.

BACKGROUND: Triple-negative breast cancer (TNBC) constitutes 10-20% of breast cancers and is challenging to treat due to a lack of effective targeted therapies. Previous studies in TNBC cell lines showed in vitro growth inhibition when JQ1 or GSK2801 were administered alone, and enhanced activity when co-administered. Given their respective mechanisms of actions, we hypothesized the combinatorial effect could be due to the target genes affected. Hence the target genes were characterized for their expression in the TNBC cell lines to prove the combinatorial effect of JQ1 and GSK2801. METHODS: RNASeq data sets of TNBC cell lines (MDA-MB-231, HCC-1806 and SUM-159) were analyzed to identify the differentially expressed genes in single and combined treatments. The topmost downregulated genes were characterized for their downregulated expression in the TNBC cell lines treated with JQ1 and GSK2801 under different dose concentrations and combinations. The optimal lethal doses were determined by cytotoxicity assays. The inhibitory activity of the drugs was further characterized by molecular modelling studies. RESULTS: Global expression profiling of TNBC cell lines using RNASeq revealed different expression patterns when JQ1 and GSK2801 were co-administered. Functional enrichment analyses identified several metabolic pathways (i.e., systemic lupus erythematosus, PI3K-Akt, TNF, JAK-STAT, IL-17, MAPK, Rap1 and signaling pathways) enriched with upregulated and downregulated genes when combined JQ1 and GSK2801 treatment was administered. RNASeq identified downregulation of PTPRC, MUC19, RNA5-8S5, KCNB1, RMRP, KISS1 and TAGLN (validated by RT-qPCR) and upregulation of GPR146, SCARA5, HIST2H4A, CDRT4, AQP3, MSH5-SAPCD1, SENP3-EIF4A1, CTAGE4 and RNASEK-C17orf49 when cells received both drugs. In addition to differential gene regulation, molecular modelling predicted binding of JQ1 and GSK2801 with PTPRC, MUC19, KCNB1, TAGLN and KISS1 proteins, adding another mechanism by which JQ1 and GSK2801 could elicit changes in metabolism and proliferation. CONCLUSION: JQ1-GSK2801 synergistically inhibits proliferation and results in selective gene regulation. Besides suggesting that combinatorial use could be useful therapeutics for the treatment of TNBC, the findings provide a glimpse into potential mechanisms of action for this combination therapy approach.

Cost Implications of Routine Preoperative Blood Typing and Crossmatching Prior to Robot-Assisted Laparoscopic Partial Nephrectomy.

INTRODUCTION: The surgical treatment of small renal masses has shifted from open to minimally invasive approaches. Preoperative blood typing and product orders often mirror the practices of the open era. We aim to define the rate of transfusion after robot-assisted partial laparoscopic nephrectomy (RAPN) at an academic medical center and the costs associated with current practice. METHODS: A retrospective review of an institutional database was utilized to identify patients who underwent RAPN and transfusion of blood products. Patient, tumor and operative variables were identified. RESULTS: From 2008 to 2021, 804 patients underwent RAPN, with 9 (1.1%) patients requiring a transfusion. Comparison of the transfused group with nontransfused patients yielded a significant difference in mean operative blood loss (527.8 ml vs 162.5 ml, p <0.0001), R.E.N.A.L. (for radius, exophytic/endophytic, nearness of tumor to collecting system, anterior/posterior, location relative to polar line) nephrometry score (7.1 vs 5.9, p <0.05), hemoglobin (11.3 gm/dl vs 13.9 gm/dl, p <0.05) and hematocrit (34.2% vs 41.4%, p <0.05). The variables associated with transfusion on univariate analysis were examined for predictive capacity using logistic regression. Operative blood loss (p <0.05), nephrometry score (p=0.05), hemoglobin (p <0.05) and hematocrit (p <0.05) remained associated with a transfusion. The hospital charge for blood typing and crossmatching was $1,320 USD per patient. CONCLUSIONS: With the maturity of RAPN techniques and outcomes, the extent of preoperative testing related to blood products should evolve to better reflect current procedural risks. Prioritizing testing resources for patients at increased complication risk can be based on predictive factors.

Perturbation of BRMS1 interactome reveals pathways that impact metastasis.

Breast Cancer Metastasis Suppressor 1 (BRMS1) expression is associated with longer patient survival in multiple cancer types. Understanding BRMS1 functionality will provide insights into both mechanism of action and will enhance potential therapeutic development. In this study, we confirmed that the C-terminus of BRMS1 is critical for metastasis suppression and hypothesized that critical protein interactions in this region would explain its function. Phosphorylation status at S237 regulates BRMS1 protein interactions related to a variety of biological processes, phenotypes [cell cycle (e.g., CDKN2A), DNA repair (e.g., BRCA1)], and metastasis [(e.g., TCF2 and POLE2)]. Presence of S237 also directly decreased MDA-MB-231 breast carcinoma migration in vitro and metastases in vivo. The results add significantly to our understanding of how BRMS1 interactions with Sin3/HDAC complexes regulate metastasis and expand insights into BRMS1's molecular role, as they demonstrate BRMS1 C-terminus involvement in distinct protein-protein interactions.

Identification of stem cells from large cell populations with topological scoring.

Machine learning and topological analysis methods are becoming increasingly used on various large-scale omics datasets. Modern high dimensional flow cytometry data sets share many features with other omics datasets like genomics and proteomics. For example, genomics or proteomics datasets can be sparse and have high dimensionality, and flow cytometry datasets can also share these features. This makes flow cytometry data potentially a suitable candidate for employing machine learning and topological scoring strategies, for example, to gain novel insights into patterns within the data. We have previously developed a Topological Score (TopS) and implemented it for the analysis of quantitative protein interaction network datasets. Here we show that TopS approach for large scale data analysis is applicable to the analysis of a previously described flow cytometry sorted human hematopoietic stem cell dataset. We demonstrate that TopS is capable of effectively sorting this dataset into cell populations and identify rare cell populations. We demonstrate the utility of TopS when coupled with multiple approaches including topological data analysis, X-shift clustering, and t-Distributed Stochastic Neighbor Embedding (t-SNE). Our results suggest that TopS could be effectively used to analyze large scale flow cytometry datasets to find rare cell populations.

Biochemical Reduction of the Topology of the Diverse WDR76 Protein Interactome.

A hub protein in protein interaction networks will typically have a large number of diverse interactions. Determining the core interactions and the function of such a hub protein remains a significant challenge in the study of networks. Proteins with WD40 repeats represent a large class of proteins that can be hub proteins. WDR76 is a poorly characterized WD40 repeat protein with possible involvement in DNA damage repair, cell-cycle progression, apoptosis, gene expression regulation, and protein quality control. WDR76 has a large and diverse interaction network that has made its study challenging. Here we rigorously carry out a series of affinity purification coupled to mass spectrometry (AP-MS) analyses to map out the WDR76 interactome through different biochemical conditions. We apply AP-MS analysis coupled to size-exclusion chromatography to resolve WDR76-based protein complexes. Furthermore, we also show that WDR76 interacts with the CCT complex via its WD40 repeat domain and with DNA-PK-KU, PARP1, GAN, SIRT1, and histones outside of the WD40 domain. An evaluation of the stability of WDR76 interactions led to focused and streamlined reciprocal analyses that validate the interactions with GAN and SIRT1. Overall, the approaches used to study WDR76 would be valuable to study other proteins containing WD40 repeat domains, which are conserved in a large number of proteins in many organisms.

Conserved abundance and topological features in chromatin-remodeling protein interaction networks.

The study of conserved protein interaction networks seeks to better understand the evolution and regulation of protein interactions. Here, we present a quantitative proteomic analysis of 18 orthologous baits from three distinct chromatin-remodeling complexes in Saccharomyces cerevisiae and Homo sapiens. We demonstrate that abundance levels of orthologous proteins correlate strongly between the two organisms and both networks have highly similar topologies. We therefore used the protein abundances in one species to cross-predict missing protein abundance levels in the other species. Lastly, we identified a novel conserved low-abundance subnetwork further demonstrating the value of quantitative analysis of networks.

Suberoylanilide hydroxamic acid (SAHA)-induced dynamics of a human histone deacetylase protein interaction network.

Histone deacetylases (HDACs) are targets for cancer therapy. Suberoylanilide hydroxamic acid (SAHA) is an HDAC inhibitor approved by the U.S. Food and Drug Administration for the treatment of cutaneous T-cell lymphoma. To obtain a better mechanistic understanding of the Sin3/HDAC complex in cancer, we extended its protein-protein interaction network and identified a mutually exclusive pair within the complex. We then assessed the effects of SAHA on the disruption of the complex network through six homologous baits. SAHA perturbs multiple protein interactions and therefore compromises the composition of large parts of the Sin3/HDAC network. A comparison of the effect of SAHA treatment on gene expression in breast cancer cells to a knockdown of the ING2 subunit indicated that a portion of the anticancer effects of SAHA may be attributed to the disruption of ING2's association with the complex. Our dynamic protein interaction network resource provides novel insights into the molecular mechanism of SAHA action and demonstrates the potential for drugs to rewire networks.

The CRAPome: a contaminant repository for affinity purification-mass spectrometry data.

Affinity purification coupled with mass spectrometry (AP-MS) is a widely used approach for the identification of protein-protein interactions. However, for any given protein of interest, determining which of the identified polypeptides represent bona fide interactors versus those that are background contaminants (for example, proteins that interact with the solid-phase support, affinity reagent or epitope tag) is a challenging task. The standard approach is to identify nonspecific interactions using one or more negative-control purifications, but many small-scale AP-MS studies do not capture a complete, accurate background protein set when available controls are limited. Fortunately, negative controls are largely bait independent. Hence, aggregating negative controls from multiple AP-MS studies can increase coverage and improve the characterization of background associated with a given experimental protocol. Here we present the contaminant repository for affinity purification (the CRAPome) and describe its use for scoring protein-protein interactions. The repository (currently available for Homo sapiens and Saccharomyces cerevisiae) and computational tools are freely accessible at http://www.crapome.org/.

Human family with sequence similarity 60 member A (FAM60A) protein: a new subunit of the Sin3 deacetylase complex.

Here we describe the function of a previously uncharacterized protein, named family with sequence similarity 60 member A (FAM60A) that maps to chromosome 12p11 in humans. We use quantitative proteomics to determine that the main biochemical partners of FAM60A are subunits of the Sin3 deacetylase complex and show that FAM60A resides in active HDAC complexes. In addition, we conduct gene expression pathway analysis and find that FAM60A regulates expression of genes that encode components of the TGF-beta signaling pathway. Moreover, our studies reveal that loss of FAM60A or another component of the Sin3 complex, SDS3, leads to a change in cell morphology and an increase in cell migration. These studies reveal the function of a previously uncharacterized protein and implicate the Sin3 complex in suppressing cell migration.

Highly reproducible label free quantitative proteomic analysis of RNA polymerase complexes.

The use of quantitative proteomics methods to study protein complexes has the potential to provide in-depth information on the abundance of different protein components as well as their modification state in various cellular conditions. To interrogate protein complex quantitation using shotgun proteomic methods, we have focused on the analysis of protein complexes using label-free multidimensional protein identification technology and studied the reproducibility of biological replicates. For these studies, we focused on three highly related and essential multi-protein enzymes, RNA polymerase I, II, and III from Saccharomyces cerevisiae. We found that label-free quantitation using spectral counting is highly reproducible at the protein and peptide level when analyzing RNA polymerase I, II, and III. In addition, we show that peptide sampling does not follow a random sampling model, and we show the need for advanced computational models to predict peptide detection probabilities. In order to address these issues, we used the APEX protocol to model the expected peptide detectability based on whole cell lysate acquired using the same multidimensional protein identification technology analysis used for the protein complexes. Neither method was able to predict the peptide sampling levels that we observed using replicate multidimensional protein identification technology analyses. In addition to the analysis of the RNA polymerase complexes, our analysis provides quantitative information about several RNAP associated proteins including the RNAPII elongation factor complexes DSIF and TFIIF. Our data shows that DSIF and TFIIF are the most highly enriched RNAP accessory factors in Rpb3-TAP purifications and demonstrate our ability to measure low level associated protein abundance across biological replicates. In addition, our quantitative data supports a model in which DSIF and TFIIF interact with RNAPII in a dynamic fashion in agreement with previously published reports.