Detailed imaging and genetic analysis reveal a secondary BRAFL505H resistance mutation and extensive intrapatient heterogeneity in metastatic BRAF mutant melanoma patients treated with vemurafenib

Resistance to treatment is the main problem of targeted treatment for cancer. We followed ten patients during treatment with vemurafenib, by three‐dimensional imaging. In all patients, only a subset of lesions progressed. Next‐generation DNA sequencing was performed on sequential biopsies in four patients to uncover mechanisms of resistance. In two patients, we identified mutations that explained resistance to vemurafenib; one of these patients had a secondary BRAF L505H mutation. This is the first observation of a secondary BRAF mutation in a vemurafenib‐resistant patient‐derived melanoma sample, which confirms the potential importance of the BRAF L505H mutation in the development of therapy resistance. Moreover, this study hints toward an important role for tumor heterogeneity in determining the outcome of targeted treatments.     

Light Intensity Physical Activity and Sedentary Behavior in Relation to Body Mass Index and Grip Strength in Older Adults: Cross-Sectional Findings from the Lifestyle Interventions and Independence for Elders (LIFE) Study

BackgroundIdentifying modifiable determinants of fat mass and muscle strength in older adults is important given their impact on physical functioning and health. Light intensity physical activity and sedentary behavior are potential determinants, but their relations to these outcomes are poorly understood. We evaluated associations of light intensity physical activity and sedentary time—assessed both objectively and by self-report—with body mass index (BMI) and grip strength in a large sample of older adults.MethodsWe used cross-sectional baseline data from 1130 participants of the Lifestyle Interventions and Independence for Elders (LIFE) study, a community-dwelling sample of relatively sedentary older adults (70-89 years) at heightened risk of mobility disability. Time spent sedentary and in light intensity activity were assessed using an accelerometer worn for 3–7 days (Actigraph GT3X) and by self-report. Associations between these exposures and measured BMI and grip strength were evaluated using linear regression.ResultsGreater time spent in light intensity activity and lower sedentary times were both associated with lower BMI. This was evident using objective measures of lower-light intensity, and both objective and self-reported measures of higher-light intensity activity. Time spent watching television was positively associated with BMI, while reading and computer use were not. Greater time spent in higher but not lower intensities of light activity (assessed objectively) was associated with greater grip strength in men but not women, while neither objectively assessed nor self-reported sedentary time was associated with grip strength.ConclusionsIn this cross-sectional study, greater time spent in light intensity activity and lower sedentary times were associated with lower BMI. These results are consistent with the hypothesis that replacing sedentary activities with light intensity activities could lead to lower BMI levels and obesity prevalence among the population of older adults. However, longitudinal and experimental studies are needed to strengthen causal inferences.     

Understanding the Impact of Hazardous and Harmful Use of Alcohol and/or Other Drugs on ARV Adherence and Disease Progression

The objective of this study was to understand the impact of hazardous and harmful use of alcohol and/or other drugs on ARV adherence and disease progression among HIV patients. A cross-sectional study design was used. A total of 1503 patients attending HIV clinics in Cape Town, South Africa were screened for problematic substance use. A sub-sample of 607 patients (303 patients who screened positive for problematic substance use and 304 who did not) participated in this study. Hazardous or harmful alcohol use and problematic drug use predicted missing and stopping ARVs which, in turn, was associated with a decrease in CD4 counts and more rapid HIV-disease progression and poorer health outcomes in people living with HIV/AIDS (PLWHA). The findings of this study underscore the need for an integrated approach to managing substance-use disorders in PLWHA.     

The Local Complement Activation on Vascular Bed of Patients with Systemic Sclerosis: A Hypothesis-Generating Study

ObjectiveThe role of complement system in the pathogenesis of systemic sclerosis (SSc) has been debated during the last decade but an evident implication in this disease has never been found. We carried out an explorative study on SSc patients to evaluate the expression of soluble and local C5b-9 complement complex and its relation with a complement regulator, the Membrane Cofactor Protein (MCP, CD46) on skin vascular bed as target distinctive of SSc disease. We also analyzed two polymorphic variants in the complement activation gene cluster involving the MCP region.MethodsC5b-9 plasma levels of SSc patients and healthy subjects were analyzed by ELISA assay. Archival skin biopsies of SSc patients and controls were subjected to immunofluorescence analysis to detect C5b-9 and MCP on vascular endothelial cells. The expression of MCP was validated by immunoblot analysis with specific antibody. Polymorphic variants in the MCP gene promoter were tested by a quantitative PCR technique-based allelic discrimination method.ResultsEven though circulating levels of C5b-9 did not differ between SSc and controls, C5b-9 deposition was detected in skin biopsies of SSc patients but not in healthy subjects. MCP was significantly lower in skin vessels of SSc patients than in healthy controls and was associated with the over-expression of two polymorphic variants in the MCP gene promoter, which has been related to more aggressive phenotypes in other immune-mediated diseases.ConclusionsOur results firsty document the local complement activation with an abnormal expression of MCP in skin vessels of SSc patients, suggesting that a subset of SSc patients might be exposed to more severe organ complications and clinical evolution due to abnormal local complement activation.     

Serotonin and Noradrenaline Reuptake Inhibitors Improve Micturition Control in Mice

Poor micturition control may cause profound distress, because proper voiding is mandatory for an active social life. Micturition results from the subtle interplay of central and peripheral components. It involves the coordination of autonomic and neuromuscular activity at the brainstem level, under the executive control of the prefrontal cortex. We tested the hypothesis that administration of molecules acting as reuptake inhibitors of serotonin, noradrenaline or both may exert a strong effect on the control of urine release, in a mouse model of overactive bladder. Mice were injected with cyclophosphamide (40 mg/kg), to increase micturition acts. Mice were then given one of four molecules: the serotonin reuptake inhibitor imipramine, its metabolite desipramine that acts on noradrenaline reuptake, the serotonin and noradrenaline reuptake inhibitor duloxetine or its active metabolite 4-hydroxy-duloxetine. Cyclophosphamide increased urine release without inducing overt toxicity or inflammation, except for increase in urothelium thickness. All the antidepressants were able to decrease the cyclophosphamide effects, as apparent from longer latency to the first micturition act, decreased number of urine spots and volume of released urine. These results suggest that serotonin and noradrenaline reuptake inhibitors exert a strong and effective modulatory effect on the control of urine release and prompt to additional studies on their central effects on brain areas involved in the social and behavioral control of micturition.     

Protectome Analysis: A New Selective Bioinformatics Tool for Bacterial Vaccine Candidate Discovery

New generation vaccines are in demand to include only the key antigens sufficient to confer protective immunity among the plethora of pathogen molecules. In the last decade, large-scale genomics-based technologies have emerged. Among them, the Reverse Vaccinology approach was successfully applied to the development of an innovative vaccine against Neisseria meningitidis serogroup B, now available on the market with the commercial name BEXSERO® (Novartis Vaccines). The limiting step of such approaches is the number of antigens to be tested in in vivo models. Several laboratories have been trying to refine the original approach in order to get to the identification of the relevant antigens straight from the genome. Here we report a new bioinformatics tool that moves a first step in this direction. The tool has been developed by identifying structural/functional features recurring in known bacterial protective antigens, the so called “Protectome space,” and using such “protective signatures” for protective antigen discovery. In particular, we applied this new approach to Staphylococcus aureus and Group B Streptococcus and we show that not only already known protective antigens were re-discovered, but also two new protective antigens were identified.Although vaccines based on attenuated pathogens as pioneered by Luis Pasteur have been shown to be extremely effective, safety and technical reasons recommend that new generation vaccines include few selected pathogen components which, in combination with immunostimulatory molecules, can induce long lasting protective responses. Such approach implies that the key antigens sufficient to confer protective immunity are singled out among the plethora of pathogen molecules. As it turns out, the search for such protective antigens can be extremely complicated.Genomic technologies have opened the way to new strategies in vaccine antigen discovery (1, 2, 3). Among them, Reverse Vaccinology (RV)¹ has proved to be highly effective, as demonstrated by the fact that a new Serogroup B Neisseria meningitidis (MenB) vaccine, incorporating antigens selected by RV, is now available to defeat meningococcal meningitis (4, 5). In essence, RV is based on the simple assumption that cloning all annotated proteins/genes and screening them against a robust and reliable surrogate-of-protection assay must lead to the identification of all protective antigens. Because most of the assays available for protective antigen selection involve animal immunization and challenge, the number of antigens to be tested represents a severe bottleneck of the entire process. For this reason, despite the fact that RV is a brute force, inclusive approach (“test-all-to-lose-nothing” type of approach) in their pioneered work of MenB vaccine discovery, Pizza and co-workers did not test the entire collection of MenB proteins but rather restricted their analysis to the ones predicted to be surface-localized. This was based on the evidence that for an anti-MenB vaccine to be protective bactericidal antibodies must be induced, a property that only surface-exposed antigens have. For the selection of surface antigens Pizza and co-workers mainly used PSORT and other available tools like MOTIFS and FINDPATTERNS to find proteins carrying localization-associated features such as transmembrane domains, leader peptides, and lipobox and outer membrane anchoring motifs. At the end, 570 proteins were selected and entered the still very labor intensive screening phase. Over the last few years, our laboratories have been trying to move to more selective strategies. Our ultimate goal, we like to refer to as the “Holy Grail of Vaccinology,” is to identify protective antigens by “simply” scanning the genome sequence of any given pathogen, thus avoiding time consuming “wet science” and “move straight from genome to the clinic” (6).With this objective in mind, we have developed a series of proteomics-based protocols that, in combination with bioinformatics tools, have substantially reduced the number of antigens to be tested in the surrogate-of-protection assays (7, 8). In particular, we have recently described a three-technology strategy that allows to narrow the number of antigens to be tested in the animal models down to less than ten (9). However, this strategy still requires high throughput experimental activities. Therefore, the availability of in silico tools that selectively and accurately single out relevant categories of antigens among the complexity of pathogen components would greatly facilitate the vaccine discovery process.In the present work, we describe a new bioinformatics approach that brings an additional contribution to our “from genome to clinic” goal. The approach has been developed on the basis of the assumption that protective antigens are protective in that they have specific structural/functional features (“protective signatures”) that distinguish them from immunologically irrelevant pathogen components. These features have been identified by using existing databases and prediction tools, such as PFam and SMART. Our approach focuses on protein biological role rather than its localization: it is completely protein localization unbiased, and lead to the identification of both surface-exposed and secreted antigens (which are the majority in extracellular bacteria) as well as cytoplasmic protective antigens (for instance, antigens that elicit interferon γ producing CD4+ T cells, thus potentiating the killing activity of phagocytic cells toward intracellular pathogens). Should these assumptions be valid, PS could be identified if: (1) all known protective antigens are compiled to create what we refer to as “the Protectome space,” and (2) Protectome is subjected to computer-assisted scrutiny using selected tools. Once signatures are identified, novel protective antigens of a pathogen of interest should be identifiable by scanning its genome sequence in search for proteins that carry one or more protective signatures. A similar attempt has been reported (10), where the discrimination of protective antigens versus nonprotective antigens was tried using statistical methods based on amino acid compositional analysis and auto cross-covariance. This model was implemented in a server for the prediction of vaccine candidates, that is, Vaxijen (www.darrenflower.info/Vaxijen); however, the selection criteria applied are still too general leading to a list of candidates that include ca. 30% of the total genome ORFs very similarly to the number of antigens predicted by classical RV based on the presence of localization signals.Here we show that Protectome analysis unravels specific signatures embedded in protective antigens, most of them related to the biological role/function of the proteins. These signatures narrow down the candidate list to ca. 3% of the total ORFs content and can be exploited for protective antigen discovery. Indeed, the strategy was validated by demonstrating that well characterized vaccine components could be identified by scanning the genome sequence of the corresponding pathogens for the presence of the PS. Furthermore, when the approach was applied to Staphylococcus aureus and Streptococcus agalactiae (Group B Streptococcus, GBS) not only already known protective antigens were rediscovered, but also two new protective antigens were identified.     

Accurate Protein Complex Retrieval by Affinity Enrichment Mass Spectrometry (AE-MS) Rather than Affinity Purification Mass Spectrometry (AP-MS)

Protein–protein interactions are fundamental to the understanding of biological processes. Affinity purification coupled to mass spectrometry (AP-MS) is one of the most promising methods for their investigation. Previously, complexes were purified as much as possible, frequently followed by identification of individual gel bands. However, todays mass spectrometers are highly sensitive, and powerful quantitative proteomics strategies are available to distinguish true interactors from background binders. Here we describe a high performance affinity enrichment-mass spectrometry method for investigating protein–protein interactions, in which no attempt at purifying complexes to homogeneity is made. Instead, we developed analysis methods that take advantage of specific enrichment of interactors in the context of a large amount of unspecific background binders. We perform single-step affinity enrichment of endogenously expressed GFP-tagged proteins and their interactors in budding yeast, followed by single-run, intensity-based label-free quantitative LC-MS/MS analysis. Each pull-down contains around 2000 background binders, which are reinterpreted from troubling contaminants to crucial elements in a novel data analysis strategy. First the background serves for accurate normalization. Second, interacting proteins are not identified by comparison to a single untagged control strain, but instead to the other tagged strains. Third, potential interactors are further validated by their intensity profiles across all samples. We demonstrate the power of our AE-MS method using several well-known and challenging yeast complexes of various abundances. AE-MS is not only highly efficient and robust, but also cost effective, broadly applicable, and can be performed in any laboratory with access to high-resolution mass spectrometers.Protein–protein interactions are key to protein-mediated biological processes and influence all aspects of life. Therefore, considerable efforts have been dedicated to the mapping of protein–protein interactions. A classical experimental approach consists of co-immunoprecipitation of protein complexes combined with SDS-PAGE followed by Western blotting to identify complex members. More recently, high-throughput techniques have been introduced; among these affinity purification-mass spectrometry (AP-MS)¹ (1–3) and the yeast two-hybrid (Y2H) approach (4–6) are the most prominent. AP-MS, in particular, has great potential for detecting functional interactions under near-physiological conditions, and has already been employed for interactome mapping in several organisms (7–15). Various AP-MS approaches have evolved over time, that differ in expression, tagging, and affinity purification of the bait protein; fractionation, LC-MS measurement, and quantification of the sample; and in data analysis. Recent progress in the AP-MS field has been driven by two factors: A new generation of mass spectrometers (16) providing higher sequencing speed, sensitivity, and mass accuracy, and the development of quantitative MS strategies.In the early days of AP-MS, tagged bait proteins were mostly overexpressed, enhancing their recovery in the pull-down. However, overexpression comes at the cost of obscuring the true situation in the cell, potentially leading to the detection of false interactions (17). Today, increased MS instrument power helps in the detection of bait proteins and interactors expressed at endogenous levels, augmenting the chances to detect functional interactions. In some simple organisms like yeast, genes of interest can directly be tagged in their genetic loci and expressed under their native promoter. In higher organisms, tagging proteins in their endogenous locus is more challenging, but also for mammalian cells, methods for close to endogenous expression are available. For instance, in controlled inducible expression systems, the concentration of the tagged bait protein can be titrated to close to endogenous levels (18). A very powerful approach is BAC transgenomics (19), as used in our QUBIC protocol (20), where a bacterial artificial chromosome (BAC) containing a tagged version of the gene of interest including all regulatory sequences and the natural promoter is stably transfected into a host cell line.The affinity purification step has also been subject to substantial changes over time. Previously, AP has been combined with nonquantitative MS as the readout, meaning all proteins identified by MS were considered potential interactors. Therefore, to reduce co-purifying “contaminants,” stringent two-step AP protocols using dual affinity tags like the TAP-tag (21) had to be employed. However, such stringent and multistep protocols can result in the loss of weak or transient interactors (3), whereas laborious and partially subjective filtering still has to be applied to clean up the list of identified proteins. The introduction of quantitative mass spectrometry (22–25) to the interactomics field about ten years ago was a paradigm shift, as it offered a proper way of dealing with unspecific binding and true interactors could be directly distinguished from background binders (26, 27). Importantly, quantification enables the detection of true interactors even under low-stringent conditions (28). In turn, this allowed the return to single-step AP protocols, which are milder and faster, and hence more suitable for detecting weak and transient interactors.Despite these advances, nonquantitative methods—often in combination with the TAP-tagging approach—are still popular and widely used, presumably because of reagent expenses and labeling protocols used in label-based approaches. However, there are ways to determine relative protein abundances in a label-free format. A simple, semiquantitative label-free way to estimate protein abundance is spectral counting (29). Another relative label-free quantification strategy is based on peptide intensities (30). In recent years high resolution MS has become much more widely accessible and there has been great progress in intensity-based label-free quantification (LFQ) approaches. Together with development of sophisticated LFQ algorithms, this has boosted obtainable accuracy. Intensity-based LFQ now offers a viable and cost-effective alternative to label-based methods in most applications (31). The potential of intensity-based LFQ approaches as tools for investigating protein–protein interactions has already been demonstrated by us (20, 32, 33) and others (34, 35). We have further refined intensity-based LFQ in the context of the MaxQuant framework (36) using sophisticated normalization algorithms, achieving excellent accuracy and robustness of the measured “MaxLFQ” intensities (37).Another important advance in AP-MS, again enabled by increased MS instrument power, was the development of single-shot LC-MS methods with comprehensive coverage. Instead of extensive fractionation, which was previously needed to reduce sample complexity, nowadays even entire model proteomes can be measured in single LC-MS runs (38). The protein mixture resulting from pull-downs is naturally of lower complexity compared with the entire proteome. Therefore, modern MS obviates the need for gel-based (or other) fractionation and samples can be analyzed in single runs. Apart from avoiding selection of gel bands by visual examination, this has many advantages, including decreased sample preparation and measurement time, increased sensitivity, and higher quantitative accuracy in a label-free format.In this work, we build on many of the recent advances in the field to establish a state of the art LFQ AE-MS method. Based on our previous QUBIC pipeline (20), we developed an approach for investigating protein–protein interactions, which we exemplify in Saccharomyces cerevisiae. We extended the data analysis pipeline to extract the wealth of information contained in the LFQ data, by establishing a novel concept that specifically makes use of the signature of background binders instead of eliminating them from the data set. The large amount of unspecific binders detected in our experiments rendered the use of a classic untagged control strain unnecessary and enabled comparing to a control group consisting of many unrelated pull-downs instead. Our protocol is generic, practical, and fast, uses low input amounts, and identifies interactors with high confidence. We propose that single-step pull-down experiments, especially when coupled to high-sensitivity MS, should now be regarded as affinity enrichment rather than affinity purification methods.     

The Human Pathogen Streptococcus pyogenes Releases Lipoproteins as Lipoprotein-rich Membrane Vesicles

Bacterial lipoproteins are attractive vaccine candidates because they represent a major class of cell surface-exposed proteins in many bacteria and are considered as potential pathogen-associated molecular patterns sensed by Toll-like receptors with built-in adjuvanticity. Although Gram-negative lipoproteins have been extensively characterized, little is known about Gram-positive lipoproteins. We isolated from Streptococcus pyogenes a large amount of lipoproteins organized in vesicles. These vesicles were obtained by weakening the bacterial cell wall with a sublethal concentration of penicillin. Lipid and proteomic analysis of the vesicles revealed that they were enriched in phosphatidylglycerol and almost exclusively composed of lipoproteins. In association with lipoproteins, a few hypothetical proteins, penicillin-binding proteins, and several members of the ExPortal, a membrane microdomain responsible for the maturation of secreted proteins, were identified. The typical lipidic moiety was apparently not necessary for lipoprotein insertion in the vesicle bilayer because they were also recovered from the isogenic diacylglyceryl transferase deletion mutant. The vesicles were not able to activate specific Toll-like receptor 2, indicating that lipoproteins organized in these vesicular structures do not act as pathogen-associated molecular patterns. In light of these findings, we propose to name these new structures Lipoprotein-rich Membrane Vesicles.Bacterial lipoproteins (Lpps)¹ are a subset of membrane proteins that are covalently modified with a lipidic moiety at their N-terminal cysteine residue. It is commonly reported that Lpps of Gram-positive bacteria are processed by two key enzymes; the prolipoprotein diacylglyceryl transferase (Lgt) and the lipoprotein signal peptidase (Lsp). The Lgt enzyme recognizes a so-called lipobox motif in the C-terminal region of the signal peptide of a premature lipoprotein and transfers a diacylglyceryl moiety to the cysteine residue of the lipobox (1), (2). Subsequently, the Lsp enzyme cleaves the signal peptide resulting in a mature Lpp (3), (4). Nevertheless, recent reports have suggested that N-acylation occurs in bacteria that lack the Gram-negative homologous apolipoprotein N-acyltransferase (Lnt) gene responsible for this modification (5, 6), and that Lpp N-terminal could also be modified with an acetyl group in some Gram-positive (7).Lpps have been described as virulence factors because they play critical roles in membrane stabilization, nutrient uptake, antibiotic resistance, bacterial adhesion to host cells, protein maturation and secretion and many of them still have unknown function (8). Several studies have suggested that bacterial Lpps are pathogen-associated molecular patterns (PAMPs) sensed by the mammalian host through Toll-like receptor 2 (TLR2) heterodimerized with TLR1 or TLR6 to induce innate immunity activation and to control adaptive immunity (9–12). TLR2 plays a critical role in the host response to the Gram-positive bacteria Staphylococcus aureus (13) and Streptococcus agalactiae (14). Although TLR2 has been considered a receptor for various structurally unrelated PAMPs, recent studies have suggested that, via their lipid moiety, bacterial Lpps function as the major, if not the sole, ligand molecules responsible for TLR2 activation (15). Although Gram-negative Lpps have been widely studied, little information is available for Gram-positive Lpps (16) and the ways they are released into the bacterial extracellular compartment and reach the host immune system remain unclear.We focused our attention on Lpps release by Streptococcus pyogenes. This Gram-positive bacterium is an important human pathogen that causes a wide range of diseases from superficial and self-limiting infection, e.g. pharyngitis and impetigo, to more systemic or invasive diseases like necrotizing fasciitis and septicemia (17). Understanding the role of bacterial Lpps in mediating innate and acquired immunity can be instrumental for the therapy and prophylaxis of human S. pyogenes infections. In this study, we showed that in S. pyogenes Lpps are released into the growth medium within vesicle-like structures in minute amounts. Conditions weakening the bacterial cell wall, such as the addition of sublethal concentrations of penicillin to the bacterial growth medium enhanced this phenomenon and allowed the recovery of sufficient material to enable an in-depth characterization. Proteomic analysis of the vesicles revealed that they were almost exclusively constituted of Lpps. A total of 28 Lpps were identified, representing more than 72% of the Lpps predicted from the genome of the strain under investigation. In addition, multiple transmembrane domain proteins were not found in abundance associated to the vesicles, indicating that vesicles were not representative of the bacterial membrane. We defined these vesicles as Lipoprotein-rich Membrane Vesicles (LMVs).Common characteristics are shared between the LMVs and the ExPortal described for the first time by Rosch and Caparon (18). This asymmetric and distinct membrane microdomain has been reported to be enriched in anionic phospholipids and acts in promoting the biogenesis of secreted proteins by coordinating interactions between nascent unfolded secretory proteins and the accessory factors required for their maturation (19–21). An association between ExPortal and peptidoglycan synthesis has also been reported (22). Similarly, LMVs are enriched in anionic phosphatidylglycerol, enzymes involved in protein maturation/secretion and cell wall biogenesis, suggesting that LMVs might derive from the ExPortal. Finally, we showed that LMVs do not induce TLR2 activation, indicating that the Lpps did not act as PAMPs when integrated into the LMVs.