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Background: Key challenges of biopsy-based determination of prostate cancer aggressiveness include tumour heterogeneity, biopsy-sampling error, and variations in biopsy interpretation. The resulting uncertainty in risk assessment leads to significant overtreatment, with associated costs and morbidity. We developed a performance-based strategy to identify protein biomarkers predictive of prostate cancer aggressiveness and lethality regardless of biopsy-sampling variation. Methods: Prostatectomy samples from a large patient cohort with long follow-up were blindly assessed by expert pathologists who identified the tissue regions with the highest and lowest Gleason grade from each patient. To simulate biopsy-sampling error, a core from a high- and a low-Gleason area from each patient sample was used to generate a ‘high’ and a ‘low’ tumour microarray, respectively. Results: Using a quantitative proteomics approach, we identified from 160 candidates 12 biomarkers that predicted prostate cancer aggressiveness (surgical Gleason and TNM stage) and lethal outcome robustly in both high- and low-Gleason areas. Conversely, a previously reported lethal outcome-predictive marker signature for prostatectomy tissue was unable to perform under circumstances of maximal sampling error. Conclusions: Our results have important implications for cancer biomarker discovery in general and development of a sampling error-resistant clinical biopsy test for prediction of prostate cancer aggressiveness.

The study of the dynamic interactome of cellular ribonucleoprotein (RNP) particles has been hampered by severe methodological limitations. In particular, the affinity purification of intact RNP complexes from cell lysates suffers from RNA degradation, loss of interacting macromolecules and poor overall yields. Here we describe a rapid affinity-purification method for efficient isolation of the subcomplexes that dynamically organize different RNP biogenesis pathways in Saccharomyces cerevisiae . Our method overcomes many of the previous limitations to produce large RNP interactomes with almost no contamination.

Human lung adenocarcinoma, the most prevalent form of lung cancer, is characterized by many molecular abnormalities. K-ras mutations are associated with the initiation of lung adenocarcinomas, but K-ras- independent mechanisms may also initiate lung tumors. Here, we find that the runt-related transcription factor Runx3 is essential for normal murine lung development and is a tumor suppressor that prevents lung adenocarcinoma. Runx3 −/− mice, which die soon after birth, exhibit alveolar hyperplasia. Importantly, Runx3 −/− bronchioli exhibit impaired differentiation, as evidenced by the accumulation of epithelial cells containing specific markers for both alveolar (that is SP-B) and bronchiolar (that is CC10) lineages. Runx3 −/− epithelial cells also express Bmi1, which supports self-renewal of stem cells. Lung adenomas spontaneously develop in aging Runx3 +/− mice (∼18 months after birth) and invariably exhibit reduced levels of Runx3. As K-ras mutations are very rare in these adenomas, Runx3 +/− mice provide an animal model for lung tumorigenesis that recapitulates the preneoplastic stage of human lung adenocarcinoma development, which is independent of K-Ras mutation. We conclude that Runx3 is essential for lung epithelial cell differentiation, and that downregulation of Runx3 is causally linked to the preneoplastic stage of lung adenocarcinoma.

Determining the subcellular localization of a protein is an important first step toward understanding its function. Here, we describe the properties of three well-known N-terminal sequence motifs directing proteins to the secretory pathway, mitochondria and chloroplasts, and sketch a brief history of methods to predict subcellular localization based on these sorting signals and other sequence properties. We then outline how to use a number of internet-accessible tools to arrive at a reliable subcellular localization prediction for eukaryotic and prokaryotic proteins. In particular, we provide detailed step-by-step instructions for the coupled use of the amino-acid sequence-based predictors TargetP, SignalP, ChloroP and TMHMM, which are all hosted at the Center for Biological Sequence Analysis, Technical University of Denmark. In addition, we describe and provide web references to other useful subcellular localization predictors. Finally, we discuss predictive performance measures in general and the performance of TargetP and SignalP in particular.

Mitochondria are an essential source of ATP for cellular function, but when damaged, mitochondria generate a plethora of stress signals, which lead to cellular dysfunction and eventually programmed cell death. Thus, a major component of maintaining cellular homeostasis is the recognition and removal of dysfunctional mitochondria through autophagy-mediated degradation, i.e., mitophagy. Mitophagy further constitutes a developmental program, and undergoes a high degree of crosstalk with apoptosis. Reduced mitochondrial quality control is linked to disease pathogenesis, suggesting the importance of process elucidation as a clinical target. Recent work has revealed multiple mitophagy programs that operate independently or undergo crosstalk, and require modulated autophagy receptor activities at outer membranes of mitochondria. Here, we review these mitophagy programs, focusing on pathway mechanisms which recognize and target mitochondria for sequestration by autophagosomes, as well as mechanisms controlling pathway activities. Furthermore, we provide an introduction to the currently available methods for detecting mitophagy.

Mass spectrometry-based proteomics empowers deep profiling of proteome and protein posttranslational modifications (PTMs) in Alzheimer’s disease (AD). Here we review the advances and limitations in historic and recent AD proteomic research. Complementary to genetic mapping, proteomic studies not only validate canonical amyloid and tau pathways, but also uncover novel components in broad protein networks, such as RNA splicing, development, immunity, membrane transport, lipid metabolism, synaptic function, and mitochondrial activity. Meta-analysis of seven deep datasets reveals 2,698 differentially expressed (DE) proteins in the landscape of AD brain proteome ( n  = 12,017 proteins/genes), covering 35 reported AD genes and risk loci. The DE proteins contain cellular markers enriched in neurons, microglia, astrocytes, oligodendrocytes, and epithelial cells, supporting the involvement of diverse cell types in AD pathology. We discuss the hypothesized protective or detrimental roles of selected DE proteins, emphasizing top proteins in “amyloidome” (all biomolecules in amyloid plaques) and disease progression. Comprehensive PTM analysis represents another layer of molecular events in AD. In particular, tau PTMs are correlated with disease stages and indicate the heterogeneity of individual AD patients. Moreover, the unprecedented proteomic coverage of biofluids, such as cerebrospinal fluid and serum, procures novel putative AD biomarkers through meta-analysis. Thus, proteomics-driven systems biology presents a new frontier to link genotype, proteotype, and phenotype, accelerating the development of improved AD models and treatment strategies.

Proteins perform most cellular functions in macromolecular complexes. The same protein often participates in different complexes to exhibit diverse functionality. Current ensemble approaches of identifying cellular protein interactions cannot reveal physiological permutations of these interactions. Here we describe a single-molecule pull-down (SiMPull) assay that combines the principles of a conventional pull-down assay with single-molecule fluorescence microscopy and enables direct visualization of individual cellular protein complexes. SiMPull can reveal how many proteins and of which kinds are present in the in vivo complex, as we show using protein kinase A. We then demonstrate a wide applicability to various signalling proteins found in the cytosol, membrane and cellular organelles, and to endogenous protein complexes from animal tissue extracts. The pulled-down proteins are functional and are used, without further processing, for single-molecule biochemical studies. SiMPull should provide a rapid, sensitive and robust platform for analysing protein assemblies in biological pathways. Protein complexes at single-molecule resolution Analysis of protein interactions is crucial for understanding cellular function and regulation. Here, Taekjip Ha and colleagues develop a novel method for elucidating the identity and stoichiometry of protein complexes from cells and tissues at single-molecule resolution. The method, called single molecule pull-down or SiMPull, can discriminate between multiple association states of a protein, and simultaneously allows determination of complex stoichiometry through photobleaching step analysis. The potential of the assay is demonstrated in a variety of contexts, including endogenous proteins from tissue extracts, organelles and membrane proteins.

Background Whole body ischemia-reperfusion injury (IRI) after cardiopulmonary resuscitation (CPR) induces a generalized inflammatory response which contributes to the development of post-cardiac arrest syndrome (PCAS). Recently, pattern recognition receptors (PRRs), such as toll-like receptors (TLRs) and inflammasomes, have been shown to mediate the inflammatory response in IRI. In this study we investigated monocyte PRR signaling and function in PCAS. Methods Blood samples were drawn in the first 12 hours, and at 24 and 48 hours following return of spontaneous circulation in 51 survivors after cardiac arrest. Monocyte mRNA levels of TLR2, TLR4, interleukin-1 receptor-associated kinase (IRAK)3, IRAK4, NLR family pyrin domain containing (NLRP)1, NLRP3, AIM2, PYCARD, CASP1, and IL1B were determined by real-time quantitative PCR. Ex vivo cytokine production in response to stimulation with TLR ligands Pam 3 CSK 4 and lipopolysaccharide (LPS) was assessed in both whole blood and monocyte culture assays. Ex vivo cytokine production of peripheral blood mononuclear cells (PBMCs) from a healthy volunteer in response to stimulation with patients’ sera with or without LPS was assessed. The results were compared to 19 hemodynamically stable patients with coronary artery disease. Results Monocyte TLR2, TLR4, IRAK3, IRAK4, NLRP3, PYCARD and IL1B were initially upregulated in patients following cardiac arrest. The NLRP1 and AIM2 inflammasomes were downregulated in resuscitated patients. There was a significant positive correlation between TLR2, TLR4, IRAK3 and IRAK4 expression and the degree of ischemia as assessed by serum lactate levels and the time until return of spontaneous circulation. Nonsurvivors at 30 days had significantly lower mRNA levels of TLR2, IRAK3, IRAK4, NLRP3 and CASP1 in the late phase following cardiac arrest. We observed reduced proinflammatory cytokine release in response to both TLR2 and TLR4 activation in whole blood and monocyte culture assays in patients after CPR. Sera from resuscitated patients attenuated the inflammatory response in cultured PBMCs after co-stimulation with LPS. Conclusions Successful resuscitation from cardiac arrest results in changes in monocyte pattern recognition receptor signaling pathways, which may contribute to the post-cardiac arrest syndrome. Trial registration The trial was registered in the German Clinical Trials Register ( DRKS00009684 ) on 27/11/2015.

Ouzounov et al . report calcium imaging with three-photon microscopy in the mouse brain. The approach enabled noninvasive recording of activity with high spatial and temporal resolution from GCaMP6-labeled neurons located as deep as the hippocampus. High-resolution optical imaging is critical to understanding brain function. We demonstrate that three-photon microscopy at 1,300-nm excitation enables functional imaging of GCaMP6s-labeled neurons beyond the depth limit of two-photon microscopy. We record spontaneous activity from up to 150 neurons in the hippocampal stratum pyramidale at ∼1-mm depth within an intact mouse brain. Our method creates opportunities for noninvasive recording of neuronal activity with high spatial and temporal resolution deep within scattering brain tissues.

Background The diagnosis of periprosthetic joint infection (PJI) remains a serious clinical challenge. There is a pressing need for improved diagnostic testing methods; biomarkers offer one potentially promising approach. Questions/purposes We evaluated the diagnostic characteristics of 16 promising synovial fluid biomarkers for the diagnosis of PJI. Methods Synovial fluid was collected from 95 patients meeting the inclusion criteria of this prospective diagnostic study. All patients were being evaluated for a revision hip or knee arthroplasty, including patients with systemic inflammatory disease and those already receiving antibiotic treatment. The Musculoskeletal Infection Society (MSIS) definition was used to classify 29 PJIs and 66 aseptic joints. Synovial fluid samples were tested by immunoassay for 16 biomarkers optimized for use in synovial fluid. Sensitivity, specificity, and receiver operating characteristic curve analysis were performed to assess for diagnostic performance. Results Five biomarkers, including human α-defensin 1-3, neutrophil elastase 2, bactericidal/permeability-increasing protein, neutrophil gelatinase-associated lipocalin, and lactoferrin, correctly predicted the MSIS classification of all patients in this study, with 100% sensitivity and specificity for the diagnosis of PJI. An additional eight biomarkers demonstrated excellent diagnostic strength, with an area under the curve of greater than 0.9. Conclusions Synovial fluid biomarkers exhibit a high accuracy in diagnosing PJI, even when including patients with systemic inflammatory disease and those receiving antibiotic treatment. Considering that these biomarkers match the results of the more complex MSIS definition of PJI, we believe that synovial fluid biomarkers can be a valuable addition to the methods utilized for the diagnosis of infection. Level of Evidence Level II, diagnostic study. See Instructions for Authors for a complete description of levels of evidence.