Protein-based Analyses Research Articles

A cost-effective protocol for single-cell RNA sequencing of human skin.

Single-cell RNA sequencing (scRNAseq) and flow cytometry studies in skin are methodologically complex and costly, limiting their accessibility to researchers worldwide. Ideally, RNA and protein-based analyses should be performed on the same lesion to obtain more comprehensive data. However, current protocols generally focus on either scRNAseq or flow cytometry of healthy skin. We present a novel label-free sample multiplexing strategy, building on the souporcell algorithm, which enables scRNAseq analysis of paired blood and skin samples. Additionally, we provide detailed instructions for simultaneous flow cytometry analysis from the same sample, with necessary adaptations for both healthy and inflamed skin specimens. This tissue multiplexing strategy mitigates technical batch effects and reduces costs by 2-4 times compared to existing protocols. We also demonstrate the effects of varying enzymatic incubation durations (1, 3, and 16 hours, with and without enzyme P) on flow cytometry outcomes. Comprehensive explanations of bioinformatic demultiplexing steps and a detailed step-by-step protocol of the entire experimental procedure are included. The protocol outlined in this article will make scRNAseq and flow cytometry analysis of skin samples more accessible to researchers, especially those new to these techniques.

A foundational approach to culture and analyze malnourished organoids

ABSTRACT The gastrointestinal (GI) epithelium plays a major role in nutrient absorption, barrier formation, and innate immunity. The development of organoid-based methodology has significantly impacted the study of the GI epithelium, particularly in the fields of mucosal biology, immunity, and host-microbe interactions. Various effects on the GI epithelium, such as genetics and nutrition, impact patients and alter disease states. Thus, incorporating these effects into organoid-based models will facilitate a better understanding of disease progression and offer opportunities to evaluate therapeutic candidates. One condition that has a significant effect on the GI epithelium is malnutrition, and studying the mechanistic impacts of malnutrition would enhance our understanding of several pathologies. Therefore, the goal of this study was to begin to develop methodology to generate viable malnourished organoids with accessible techniques and resources that can be used for a wide array of mechanistic studies. By selectively limiting distinct macronutrient components of organoid media, we were able to successfully culture and evaluate malnourished organoids. Genetic and protein-based analyses were used to validate the approach and confirm the presence of known biomarkers of malnutrition. Additionally, as proof-of-concept, we utilized malnourished organoid-derived monolayers to evaluate the effect of malnourishment on barrier formation and the ability of the bacterial pathogen Shigella flexneri to infect the GI epithelium. This work serves as the basis for new and exciting techniques to alter the nutritional state of organoids and investigate the related impacts on the GI epithelium.

Whole-exome analyses of congenital muscular dystrophy and congenital myopathy patients from India reveal a wide spectrum of known and novel mutations.

Congenital muscular dystrophies (CMDs) and congenital myopathies (CMs) are a group of genetically and clinically heterogeneous degenerative primary muscle disorders with onset at birth or during infancy. Due to vast heterogeneity, clinical examination and protein-based analyses often fail to identify the genetic causes of these diseases. The aim of this study was to genetically diagnose a cohort of 36 difficult-to-diagnose CMD and CM cases of Indian origin using next-generation sequencing methods. Whole-exome sequencing (WES) was performed to identify pathogenic mutations in previously reported CMD and CM-related genes using variant calling and stringent variant filtration process. Subsequently, in silico homology modelling and molecular dynamics simulations (MDS) studies were undertaken for a number of novel and missense variants. A total of 33 and 21 rare and deleterious mutations were identified in 28 genes previously reported in CMD and CM based on OMIM, ClinVar and Orphanet, respectively. We could accurately diagnose 54% patients (n=12/22) in the CMD group and 35% patients (n=5/14) in the CM group. Furthermore, MDS studies for mutations located in LMNA, LAMA2 and RYR1 suggest that the wild-type proteins are more stable than their mutant counterparts, implying a potential mechanism of pathogenesis. The WES findings led us to identify reported as well as novel variants for the first time in Indian patients with CMD and CM. This allowed us to achieve an accurate genetic diagnosis, which was difficult using conventional diagnostic tools. Transferring these WES findings to clinical practice will help guide clinical care of the affected patients and inform genetic counselling.

VIRIDIC-A Novel Tool to Calculate the Intergenomic Similarities of Prokaryote-Infecting Viruses.

Nucleotide-based intergenomic similarities are useful to understand how viruses are related with each other and to classify them. Here we have developed VIRIDIC, which implements the traditional algorithm used by the International Committee on Taxonomy of Viruses (ICTV), Bacterial and Archaeal Viruses Subcommittee, to calculate virus intergenomic similarities. When compared with other software, VIRIDIC gave the best agreement with the traditional algorithm, which is based on the percent identity between two genomes determined by BLASTN. Furthermore, VIRIDIC proved best at estimating the relatedness between more distantly-related phages, relatedness that other tools can significantly overestimate. In addition to the intergenomic similarities, VIRIDIC also calculates three indicators of the alignment ability to capture the relatedness between viruses: the aligned fractions for each genome in a pair and the length ratio between the two genomes. The main output of VIRIDIC is a heatmap integrating the intergenomic similarity values with information regarding the genome lengths and the aligned genome fraction. Additionally, VIRIDIC can group viruses into clusters, based on user-defined intergenomic similarity thresholds. The sensitivity of VIRIDIC is given by the BLASTN. Thus, it is able to capture relationships between viruses having in common even short genomic regions, with as low as 65% similarity. Below this similarity level, protein-based analyses should be used, as they are the best suited to capture distant relationships. VIRIDIC is available at viridic.icbm.de, both as a web-service and a stand-alone tool. It allows fast analysis of large phage genome datasets, especially in the stand-alone version, which can be run on the user’s own servers and can be integrated in bioinformatics pipelines. VIRIDIC was developed having viruses of Bacteria and Archaea in mind; however, it could potentially be used for eukaryotic viruses as well, as long as they are monopartite.

Widespread Translational Control of Fibrosis in the Human Heart by RNA-Binding Proteins.

Fibrosis is a common pathology in many cardiac disorders and is driven by the activation of resident fibroblasts. The global posttranscriptional mechanisms underlying fibroblast-to-myofibroblast conversion in the heart have not been explored. Genome-wide changes of RNA transcription and translation during human cardiac fibroblast activation were monitored with RNA sequencing and ribosome profiling. We then used RNA-binding protein-based analyses to identify translational regulators of fibrogenic genes. The integration with cardiac ribosome occupancy levels of 30 dilated cardiomyopathy patients demonstrates that these posttranscriptional mechanisms are also active in the diseased fibrotic human heart. We generated nucleotide-resolution translatome data during the transforming growth factor β1-driven cellular transition of human cardiac fibroblasts to myofibroblasts. This identified dynamic changes of RNA transcription and translation at several time points during the fibrotic response, revealing transient and early-responder genes. Remarkably, about one-third of all changes in gene expression in activated fibroblasts are subject to translational regulation, and dynamic variation in ribosome occupancy affects protein abundance independent of RNA levels. Targets of RNA-binding proteins were strongly enriched in posttranscriptionally regulated genes, suggesting genes such as MBNL2 can act as translational activators or repressors. Ribosome occupancy in the hearts of patients with dilated cardiomyopathy suggested the same posttranscriptional regulatory network was underlying cardiac fibrosis. Key network hubs include RNA-binding proteins such as Pumilio RNA binding family member 2 (PUM2) and Quaking (QKI) that work in concert to regulate the translation of target transcripts in human diseased hearts. Furthermore, silencing of both PUM2 and QKI inhibits the transition of fibroblasts toward profibrotic myofibroblasts in response to transforming growth factor β1. We reveal widespread translational effects of transforming growth factor β1 and define novel posttranscriptional regulatory networks that control the fibroblast-to-myofibroblast transition. These networks are active in human heart disease, and silencing of hub genes limits fibroblast activation. Our findings show the central importance of translational control in fibrosis and highlight novel pathogenic mechanisms in heart failure.

Rapid Isolation of Total Protein from Arabidopsis Pollen.

Arabidopsis pollen is an excellent system for answering important biological questions about the establishment and maintenance of cellular polarity and polar cell growth, because these processes are amenable to the genetic and genomic approaches that are readily available in Arabidopsis. Given that proteins are the direct executors of a wide variety of cellular processes, it is important to rapidly and efficiently isolate total protein for various protein-based analyses, such as Western blotting, co-immunoprecipitation and mass spectrometry, among others. Here we present a protocol for rapid isolation of total protein from Arabidopsis pollen, which is adapted from our recently published paper (Chang and Huang, 2015).

Use of Whole-Exome Sequencing for Diagnosis of Limb-Girdle Muscular Dystrophy

To our knowledge, the efficacy of transferring next-generation sequencing from a research setting to neuromuscular clinics has never been evaluated. To translate whole-exome sequencing (WES) to clinical practice for the genetic diagnosis of a large cohort of patients with limb-girdle muscular dystrophy (LGMD) for whom protein-based analyses and targeted Sanger sequencing failed to identify the genetic cause of their disorder. We performed WES on 60 families with LGMDs (100 exomes). Data analysis was performed between January 6 and December 19, 2014, using the xBrowse bioinformatics interface (Broad Institute). Patients with LGMD were ascertained retrospectively through the Institute for Neuroscience and Muscle Research Biospecimen Bank between 2006 and 2014. Enrolled patients had been extensively investigated via protein studies and candidate gene sequencing and remained undiagnosed. Patients presented with more than 2 years of muscle weakness and with dystrophic or myopathic changes present in muscle biopsy specimens. The diagnostic rate of LGMD in Australia and the relative frequencies of the different LGMD subtypes. Our central goals were to improve the genetic diagnosis of LGMD, investigate whether the WES platform provides adequate coverage of known LGMD-related genes, and identify new LGMD-related genes. With WES, we identified likely pathogenic mutations in known myopathy genes for 27 of 60 families. Twelve families had mutations in known LGMD-related genes. However, 15 families had variants in disease-related genes not typically associated with LGMD, highlighting the clinical overlap between LGMD and other myopathies. Common causes of phenotypic overlap were due to mutations in congenital muscular dystrophy-related genes (4 families) and collagen myopathy-related genes (4 families). Less common myopathies included metabolic myopathy (2 families), congenital myasthenic syndrome (DOK7), congenital myopathy (ACTA1), tubular aggregate myopathy (STIM1), myofibrillar myopathy (FLNC), and mutation of CHD7, usually associated with the CHARGE syndrome. Inclusion of family members increased the diagnostic efficacy of WES, with a diagnostic rate of 60% for "trios" (an affected proband with both parents) vs 40% for single probands. A follow-up screening of patients whose conditions were undiagnosed on a targeted neuromuscular disease-related gene panel did not improve our diagnostic yield. With WES, we achieved a diagnostic success rate of 45.0% in our difficult-to-diagnose cohort of patients with LGMD. We expand the clinical phenotypes associated with known myopathy genes, and we stress the importance of accurate clinical examination and histopathological results for interpretation of WES, with many diagnoses requiring follow-up review and ancillary investigations of biopsy specimens or serum samples.

Efficient Expression and Immunoaffinity Purification of Human Trace Amine-Associated Receptor 5 from E. coli Cell-Free System

G protein-coupled receptors (GPCRs) represent attractive targets for bioactive and drug discovery programs. The availability of purified receptors in milligram quantities is essential to spur the advancement of protein-based analyses in these programs, although it is still a challenging goal to achieve. Here we report the production of a bioengineered GPCR of human trace amine-associated receptor 5 (hTAAR5) from an E. coli cell-free system. Both the hTAAR5 and hTAAR5-T4 lysozyme fusion proteins (hTAAR5-T4L) were cloned and expressed in this process, with the latter designed for further protein crystallization trials. The detergent Brij-35 was found to solubilize the produced hTAAR5 and hTAAR5-T4L effectively. Immunoaffinity purification in combination with gel filtration was employed to purify the receptors to high homogeneity. The final yields of monomeric hTAAR5 and hTAAR5-T4L from a 1 mL cell-free reaction were 0.4 mg and 0.5 mg, respectively. Circular Dichroism (CD) spectroscopy indicated that both hTAAR5 and hTAAR5- T4L were correctly folded after purification, with characteristic high α-helical contents ( > 45%).

Metagenomic Analyses: Past and Future Trends

Metagenomics has revolutionized microbiology by paving the way for a cultivation-independent assessment and exploitation of microbial communities present in complex ecosystems. Metagenomics comprising construction and screening of metagenomic DNA libraries has proven to be a powerful tool to isolate new enzymes and drugs of industrial importance. So far, the majority of the metagenomically exploited habitats comprised temperate environments, such as soil and marine environments. Recently, metagenomes of extreme environments have also been used as sources of novel biocatalysts. The employment of next-generation sequencing techniques for metagenomics resulted in the generation of large sequence data sets derived from various environments, such as soil, the human body, and ocean water. Analyses of these data sets opened a window into the enormous taxonomic and functional diversity of environmental microbial communities. To assess the functional dynamics of microbial communities, metatranscriptomics and metaproteomics have been developed. The combination of DNA-based, mRNA-based, and protein-based analyses of microbial communities present in different environments is a way to elucidate the compositions, functions, and interactions of microbial communities and to link these to environmental processes.

Phylogenetic and proteomic analysis of an anaerobic toluene-degrading community

This study intended to unravel the physiological interplay in an anaerobic microbial community that degrades toluene under sulfate-reducing conditions combining proteomic and genetic techniques. An enriched toluene-degrading community (Zz5-7) growing in batch cultures was investigated by DNA- and protein-based analyses. The affiliation and diversity of the community were analysed using 16S ribosomal RNA (rRNA) genes as a phylogenetic marker as well as bssA and dsrAB genes as functional markers. Metaproteome analysis was carried out by a global protein extraction and a subsequent protein separation by two-dimensional gel electrophoresis (2-DE). About 85% of the proteins in the spots were identified by nano-liquid chromatography coupled with electrospray mass spectrometry (nano-LC-ESI-MS/MS) analysis. DNA sequencing of bssA and the most abundant dsrAB amplicons revealed high similarities to a member of the Desulfobulbaceae, which was also predominant according to 16S rRNA gene amplicons. Metaproteome analysis provided 202 unambiguous protein identifications derived from 236 unique protein spots. The proteins involved in anaerobic toluene activation, dissimilatory sulfate reduction, hydrogen production/consumption and autotrophic carbon fixation were mainly affiliated to members of the Desulfobulbaceae and several other Deltaproteobacteria. Phylogenetic and metaproteomic analyses revealed a member of the Desulfobulbaceae as the key player of anaerobic toluene degradation in a sulfate-reducing consortium. This is the first study that combines genetic and proteomic analyses to indicate the interactions in an anaerobic toluene-degrading microbial consortium.

Sweetening the Pot: Adding Glycosylation to the Biomarker Discovery Equation

Cancer has profound effects on gene expression, including a cell's glycosylation machinery. Thus, tumors produce glycoproteins that carry oligosaccharides with structures that are markedly different from the same protein produced by a normal cell. A single protein can have many glycosylation sites that greatly amplify the signals they generate compared with their protein backbones. In this article, we survey clinical tests that target carbohydrate modifications for diagnosing and treating cancer. We present the biological relevance of glycosylation to disease progression by highlighting the role these structures play in adhesion, signaling, and metastasis and then address current methodological approaches to biomarker discovery that capitalize on selectively capturing tumor-associated glycoforms to enrich and identify disease-related candidate analytes. Finally, we discuss emerging technologies--multiple reaction monitoring and lectin-antibody arrays--as potential tools for biomarker validation studies in pursuit of clinically useful tests. The future of carbohydrate-based biomarker studies has arrived. At all stages, from discovery through verification and deployment into clinics, glycosylation should be considered a primary readout or a way of increasing the sensitivity and specificity of protein-based analyses.

Gene Sequence Phylogenies of the Family Microbacteriaceae

The type strains of 32 species of 13 genera of the family Microbacteriaceae were analysed with respect to gene-coding phylogeny for DNA gyrase subunit B (gyrB), RNA-polymerase subunit B (rpoB), recombinase A (recA), and polyphosphate kinase (ppk). The resulting gene trees were compared with the 16S rRNA gene phylogeny of the same strains. The topology of neighbour-joining and maximum parsimony phylogenetic trees, based on nucleic-acid sequences and protein sequences of housekeeping genes, differed from one another, and no gene tree was identical to that of the 16S rRNA gene tree. Most genera analysed containing >1 strain formed phylogenetically coherent taxa. The three pathovars of Curtobacterium flaccumfaciens clustered together to the exclusion of the type strains of other Curtobacterium species in all DNA - and protein-based analyses. In no tree did the distribution of a major taxonomic marker, i.e., diaminobutyric acid versus lysine and/or ornithine in the peptidoglycan, or acyl type of peptidoglycan, correlate with the phylogenetic position of the organisms. The changing phylogenetic position of Agrococcus jenensis was unexpected: This strain defined individual lineages in the trees based on 16S rRNA and gyrB and showed identity with Microbacterium saperdae in the other three gene trees.

How Much of the Proteome Do We See with Discovery-Based Proteomics Methods and How Much Do We Need to See?

Despite the recent advances in parallel protein-based analyses the proportion of the protein composition of any specific tissue or organism that is currently being analyzed is still unknown. The ultimate aim of proteomics is to characterize all of the proteins in a biological system under study, but much has been gained from knowledge of smaller subsets of the proteome. Therefore, while techniques and instrumentation are being improved to increase the sensitivity of analysis, it is just as important to answer the question of what depth of analysis is required for reasonable conclusions to be reached. The questions to be answered and the resulting depth of analysis required will vary depending upon whether the understanding is required for diagnostic markers, therapeutic targets or biological systems. The issues associated with increasing the depth of analysis of proteins in the context of these areas will be discussed. However, it should be noted that merely increasing the amount of data acquired will not necessarily increase the amount of knowledge of a particular system and as such careful implementation of proteomic methods is required to advance these fields of research.

Proteomics: evolution of the technology.

INTRODUCTIONTechnologies enable the advancement of science, which is a process that has been repeated many times throughout the history of science. One of these recent enabling tech-nologies is proteomics. It is an “overnight” sensation that was more than two decades in the making, being developed in a similar time frame as this publication, BioTechniques. Proteomics is the term applied to parallel protein-based analyses. Originally used to describe two-dimensional gel electrophoresis (2-DE) and mass spectrometric analyses of proteins of interest, the term has been applied to any parallel protein analysis method—and even some that really aren’t. This article focuses on parallel protein analyses that result in the identification of components within a system (profil-ing), their posttranslational modifications and/or quantitative analyses of the amounts of the proteins, and modifications or activities, rather than other fields that come under the banner of proteomics, such as structural biology methods that have been reviewed elsewhere (1). We will address how these tech-nologies have impacted science to date and how they might have an impact in the future.WHERE HAVE WE COME FROM?To get to where we are now, a quick glimpse at the past with a couple of limited examples is warranted. Note that this perspective is not intended as a comprehensive review, so only a few pertinent references will be cited per section. There are several recent review articles in the field that pro-vide more in-depth coverage (2,3). Reports of 2-DE, as we know it today, were published in 1975 by three groups and provided the first glimpse at the complexity of the protein content of cells and, as such, can be thought of as marking the true beginning of proteomics (4–6), almost 20 years before the term “proteomics” was coined. It is still the highest resolution protein separation method avail-able and provided the first means of interrogating the levels of hundreds of proteins and their isoforms. However, in 1975, the ability to identify the proteins that displayed an interest-ing regulation proved difficult. Determining the relative in-tensity of the hundreds of spots between numerous gels was also problematic (as was the reproducibility of the method). Automated protein sequencers that could analyze the amount of protein in 2-DE spots had not been developed at that time (that occurred during the following decade), algorithms for image analysis were at an early stage, and computers that could handle the large amounts of data that multiple high-resolution images contained did not yet exist. Several prob-lems had to be solved before this technology could provide answers to detailed biological questions. However, even in its nascent form, discoveries were made, such as the oscillating levels of proliferating cell nuclear antigens (PCNAs) during the cell cycle observed from cell biology experiments in the 1980s (7,8). Protein-DNA interaction studies also revealed the fos-jun interaction (9). However, the full impact of the technology was still limited because it was mostly conducted in the laboratories of a relatively few practitioners of the art. For that to change, a number of advances had to be made, in-cluding some indirectly associated with the field.The advances that enabled proteomics can be thought of as 4-fold (Figure 1). (i) Image analysis methods needed to improve, as did the reproducibility of the 2-DE method, both of which continue to this day. (ii) A method for the sensitive identification of gel-separated proteins was required that ad-vances in mass spectrometry (MS) provided in the late 1980s. (iii) The content of the sequence databases exploded initially with the large-scale expressed sequence tag (EST) sequenc-ing efforts in both the public and private domains and sub-sequently in genomic sequencing efforts. (iv) Computational methods for the correlation of the results of mass spectro-metric analyses with the content of sequence databases were developed. These advances all occurred in the early 1990s, and in 1994, at the first 2-DE meeting in Siena, Italy, the term “proteome” was coined, short for the “protein complement of the genome” (10). The time was right to spark renewed inter-est in this field, which had been so promising for so many years, but had yet to enter the mainstream of biological analy-ses. During the 1990s, the realization of the genomics revolu-tion was taking place, and the potential for true global-scale analyses was becoming a reality with methods such as yeast two-hybrid analysis coming to the fore, and the improvement of EST and genomic sequencing efforts (11).Before the introduction of these technologies, reduction-ist approaches were often employed in the pursuit of the individual proteins or protein families that contributed to an activity/pathway of interest in hypothesis-driven research

The potential use of laser capture microdissection to selectively obtain distinct populations of cells for proteomic analysis--preliminary findings.

Proteomics-based studies offer a powerful complementary approach to DNA/RNA-based investigations and are now being applied to investigate aspects of many diseases including cancer. However, the heterogeneous nature of tissue samples often makes interpretation difficult. We have undertaken a study into the potential use of a novel laser capture microdissection (LCM) system to isolate cells of interest for subsequent proteomic analysis. Retrieval of selected cells is achieved by activation of a transfer film placed in contact with a tissue section, by a laser beam (30 or 60 microm diameter) which is focused on a selected area of tissue using an inverted microscope. The precise area of film targeted by the laser bonds to the tissue beneath it and these cells are then lifted free of surrounding tissue. Although the technique has been shown to be readily compatible with subsequent analysis of nucleic acids, little information is yet available regarding the application of protein-based analyses to the captured tissue. We report here preliminary data regarding the potential use of the LCM system in combination with two-dimensional electrophoresis to examine protein profiles of selected tissue areas. Electrophoretic profiles of proteins from normal and malignant renal tissue samples showed little change following LCM, nine selected proteins showed identical mass spectrometric sequencing profiles, and two selected proteins retained antigenicity. Dissection of epithelial tissue from a sample of normal human cervix resulted in enrichment of some proteins compared with analysis of the whole tissue. LCM will be a valuable adjunct to proteomic studies although further detailed validation is necessary.