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Understanding the tissue-specific genetic controls of protein levels is essential to uncover mechanisms of post-transcriptional gene regulation. In this study, we generated a genomic atlas of protein levels in three tissues relevant to neurological disorders (brain, cerebrospinal fluid and plasma) by profiling thousands of proteins from participants with and without Alzheimer’s disease. We identified 274, 127 and 32 protein quantitative trait loci (pQTLs) for cerebrospinal fluid, plasma and brain, respectively. cis-pQTLs were more likely to be tissue shared, but trans-pQTLs tended to be tissue specific. Between 48.0% and 76.6% of pQTLs did not co-localize with expression, splicing, DNA methylation or histone acetylation QTLs. Using Mendelian randomization, we nominated proteins implicated in neurological diseases, including Alzheimer’s disease, Parkinson’s disease and stroke. This first multi-tissue study will be instrumental to map signals from genome-wide association studies onto functional genes, to discover pathways and to identify drug targets for neurological diseases. Yang et al. generated a genomic atlas of protein levels in brain, cerebrospinal fluid and plasma and used human genetics approaches to identify proteins implicated in neurological diseases as well as druggable targets.

Screening drugs on patient biopsies from solid tumours has immense potential, but is challenging due to the small amount of available material. To address this, we present here a plug-based microfluidics platform for functional screening of drug combinations. Integrated Braille valves allow changing the plug composition on demand and enable collecting >1200 data points (56 different conditions with at least 20 replicates each) per biopsy. After deriving and validating efficient and specific drug combinations for two genetically different pancreatic cancer cell lines and xenograft mouse models, we additionally screen live cells from human solid tumours with no need for ex vivo culturing steps, and obtain highly specific sensitivity profiles. The entire workflow can be completed within 48 h at assay costs of less than US$ 150 per patient. We believe this can pave the way for rapid determination of optimal personalized cancer therapies. Cancer patients exhibit specific sensitivities toward drug combinations that cannot be easily predicted. Here the authors setup a microfluidic platform that allows testing of multiple drug combinations correctly predicting sensitivity in vivo and they use it on patients biopsies to define effective drugs.

Single-cell analysis reveals aspects of cellular physiology not evident from population-based studies, particularly in the case of highly multiplexed methods such as mass cytometry (CyTOF) able to correlate the levels of multiple signalling, differentiation and cell fate markers. Immunofluorescence (IF) microscopy adds information on cell morphology and the microenvironment that are not obtained using flow-based techniques, but the multiplicity of conventional IF is limited. This has motivated development of imaging methods that require specialized instrumentation, exotic reagents or proprietary protocols that are difficult to reproduce in most laboratories. Here we report a public-domain method for achieving high multiplicity single-cell IF using cyclic immunofluorescence (CycIF), a simple and versatile procedure in which four-colour staining alternates with chemical inactivation of fluorophores to progressively build a multichannel image. Because CycIF uses standard reagents and instrumentation and is no more expensive than conventional IF, it is suitable for high-throughput assays and screening applications. Multiplexed single cell measurements provide insight into connections between cell state and phenotype. Here Lin et al. present CycIF, a high throughput, public domain immunofluorescence method for multiplexed single-cell analysis of adherent cells following live-cell imaging.

PurposeCharacterizing submicron protein particles (approximately 0.1–1μm) is challenging due to a limited number of suitable instruments capable of monitoring a relatively large continuum of particle size and concentration. In this work, we report for the first time the characterization of submicron protein particles using the high size resolution technique of resistive pulse sensing (RPS).MethodsResistive pulse sensing, dynamic light scattering and size-exclusion chromatography with in-line multi-angle light scattering (SEC-MALS) are performed on protein and placebo formulations, polystyrene size standards, placebo formulations spiked with silicone oil, and protein formulations stressed via freeze-thaw cycling, thermal incubation, and acid treatment.ResultsA method is developed for monitoring submicron protein particles using RPS. The suitable particle concentration range for RPS is found to be approximately 4 × 107-1 × 1011 particles/mL using polystyrene size standards. Particle size distributions by RPS are consistent with hydrodynamic diameter distributions from batch DLS and to radius of gyration profiles from SEC-MALS. RPS particle size distributions provide an estimate of particle counts and better size resolution compared to light scattering.ConclusionRPS is applicable for characterizing submicron particles in protein formulations with a high degree of size polydispersity. Data on submicron particle distributions provide insights into particles formation under different stresses encountered during biologics drug development.

Cell-based assays for compound screening and profiling are fundamentally important in life sciences, chemical biology and pharmaceutical research. Most cell assays measure the amount of a single reporter molecule or cellular endpoint, and require the use of fluorescence or other labeled materials. Consequently, there is high demand for label-free technologies that enable multiple biomolecules or endpoints to be measured simultaneously. Here, we describe how to develop, optimize and validate MALDI-TOF mass spectrometry (MS) cell assays that can be used to measure cellular uptake of transporter substrates, to monitor cellular drug target engagement or to discover cellular drug-response markers. In uptake assays, intracellular accumulation of a transporter substrate and its inhibition by test compounds is measured. In drug response assays, changes to multiple cellular metabolites or to abundant posttranslational protein modifications are monitored as reporters of drug activity. We detail a ten-part optimization protocol with every part taking 1–2 d that leads to a final 2 d optimized procedure, which includes cell treatment, transfer, MALDI MS-specific sample preparation, quantification using stable-isotope-labeled standards, MALDI-TOF MS data acquisition, data processing and analysis. Key considerations for validation and automation of MALDI-TOF MS cell assays are outlined. Overall, label-free MS cell-based assays offer speed, sensitivity, accuracy and versatility in drug research. MALDI-TOF mass spectrometry (MS) can detect multiple compounds simultaneously. This protocol describes how to develop and optimize high-throughput, cell-based assays that use MALDI-TOF MS to detect drug uptake or biochemical markers of drug activity.

Historically, soil-transmitted helminth (STH) control and prevention strategies have relied on mass drug administration efforts targeting preschool and school-aged children. While these efforts have succeeded in reducing morbidity associated with STH infection, recent modeling efforts have suggested that expanding intervention to treatment of the entire community could achieve transmission interruption in some settings. Testing the feasibility of such an approach requires large-scale clinical trials, such as the DeWorm3 cluster randomized trial. In addition, accurate interpretation of trial outcomes requires diagnostic platforms capable of accurately determining infection prevalence (particularly as infection intensity is reduced) at large population scale and with significant throughput. Here, we describe the development and validation of such a high-throughput molecular testing platform. Through the development, selection, and validation of appropriate controls, we have successfully created and evaluated the performance of a testing platform capable of the semi-automated, high-throughput detection of four species of STH in human stool samples. Comparison of this platform with singleplex reference assays for the detection of these same pathogens has demonstrated comparable performance metrics, with index assay accuracy measuring at or above 99.5% and 98.1% for each target species at the level of the technical replicate and individual extraction respectively. Through the implementation of a rigorous validation program, we have developed a diagnostic platform capable of providing the necessary throughput and performance required to meet the needs of the DeWorm3 cluster randomized trial and other large-scale operational research efforts for STH. Resulting from the rigorous developmental approach taken, the platform we describe here provides the needed confidence in testing outcomes when utilized in conjunction with large-scale efforts such as the DeWorm3 trial. Additionally, the successful development of an evaluation and validation strategy provides a template for the creation of similar diagnostic platforms for other neglected tropical diseases.

There are thousands of known cellular phosphorylation sites, but the paucity of ways to identify kinases for particular phosphorylation events remains a major roadblock for understanding kinase signaling. To address this, we here develop a generally applicable method that exploits the large number of kinase inhibitors that have been profiled on near-kinome-wide panels of protein kinases. The inhibition profile for each kinase provides a fingerprint that allows identification of unknown kinases acting on target phosphosites in cell extracts. We validate the method on diverse known kinase-phosphosite pairs, including histone kinases, EGFR autophosphorylation, and Integrin β1 phosphorylation by Src-family kinases. We also use our approach to identify the previously unknown kinases responsible for phosphorylation of INCENP at a site within a commonly phosphorylated motif in mitosis (a non-canonical target of Cyclin B-Cdk1), and of BCL9L at S915 (PKA). We show that the method has clear advantages over in silico and genetic screening. Identifying kinases responsible for specific phosphorylation events remains challenging. Here, the authors leverage kinase inhibitor profiles for the identification of kinase-substrate site pairs in cell extracts, developing a method that can identify the enzymes responsible for unassigned phosphorylation events.

One quantitative liquid handling method in conventional assay processes is pipetting, which delivers a precise volume of one sample at a time. As this process becomes laborious and time-consuming as the number of samples increases, researchers in individual laboratories need a way to conduct large-scale assays in a reasonable amount of time and at an affordable cost. Here we report a novel handling technique of chemical substances termed ‘partipetting’, which allows the one-step pipetting of various chemical-laden hydrogels. We pipette and assemble various types of encoded chemical-laden microparticles in microwell arrays in parallel. The combination of this heterogeneous particle chip and a cell chip induces the release of the chemicals from the hydrogels and, eventually, the chemicals treat the targets. Based on bioassay applications using partipetting, we show its capability in large-scale bioassays, without the need for high-throughput bioassay resources, owing to a reduction in the assay costs and time. High-throughput screening allows for the rapid assessment of biochemical compounds and processes, but with increasing scale comes increasing costs. Here, the authors use an array of lithographically encoded hydrogel microparticles as a more accessible screening technique.

The lack of reproducibility with animal phenotyping experiments is a growing concern among the biomedical community. One contributing factor is the inadequate description of statistical analysis methods that prevents researchers from replicating results even when the original data are provided. Here we present PhenStat--a freely available R package that provides a variety of statistical methods for the identification of phenotypic associations. The methods have been developed for high throughput phenotyping pipelines implemented across various experimental designs with an emphasis on managing temporal variation. PhenStat is targeted to two user groups: small-scale users who wish to interact and test data from large resources and large-scale users who require an automated statistical analysis pipeline. The software provides guidance to the user for selecting appropriate analysis methods based on the dataset and is designed to allow for additions and modifications as needed. The package was tested on mouse and rat data and is used by the International Mouse Phenotyping Consortium (IMPC). By providing raw data and the version of PhenStat used, resources like the IMPC give users the ability to replicate and explore results within their own computing environment.

Directed evolution has become an important method to unleash the latent potential of enzymes to make them uniquely suited for human purposes. However, the need for a large reagent volume and sophisticated instrumentation hampers its broad implementation. In an attempt to address this problem, here we report a paper-based high-throughput screening approach that should find broad application in generating desired enzymes. As an example case, the dehalogenation reaction of the halohydrin dehalogenase was adopted for assay development. In addition to visual detection, quantitative measurements were performed by measuring the color intensity of an image that was photographed by a smartphone and processed using ImageJ free software. The proposed method was first validated using a gold standard method and then applied to mutagenesis library screening with reduced consumption of reagents (i.e., ≤ 10 μl per assay) and a shorter assay time. We identified two active mutants (P135A and G137A) with improved activities toward four tested substrates. The assay not only consumes less reagents but also eliminates the need for expensive instrumentation. The proposed method demonstrates the potential of paper-based whole-cell screening coupled with digital image colorimetry as a promising approach for the discovery of industrially important enzymes.Key Points• A frugal method was developed for directed enzyme evolution.• Mutagenesis libraries were successfully screened on a paper platform.• Smartphone imaging was efficiently used to measure enzyme activities.