Crossword: A Fully Automated Algorithm for the Segmentation and Quality Control of Protein Microarray Images

Biological assays formatted as microarrays have become a critical tool for the generation of the comprehensive data sets required for systems-level understanding of biological processes. Manual annotation of data extracted from images of microarrays, however, remains a significant bottleneck, particularly for protein microarrays due to the sensitivity of this technology to weak artifact signal. In order to automate the extraction and curation of data from protein microarrays, we describe an algorithm called Crossword that logically combines information from multiple approaches to fully automate microarray segmentation. Automated artifact removal is also accomplished by segregating structured pixels from the background noise using iterative clustering and pixel connectivity. Correlation of the location of structured pixels across image channels is used to identify and remove artifact pixels from the image prior to data extraction. This component improves the accuracy of data sets while reducing the requirement for time-consuming visual inspection of the data. Crossword enables a fully automated protocol that is robust to significant spatial and intensity aberrations. Overall, the average amount of user intervention is reduced by an order of magnitude and the data quality is increased through artifact removal and reduced user variability. The increase in throughput should aid the further implementation of microarray technologies in clinical studies.Camille and Henry Dreyfus Foundation (Camille Dreyfus Teacher-Scholar Award

Single-Cell Detection of Secreted A and sAPP from Human IPSC-Derived Neurons and Astrocytes

Secreted factors play a central role in normal and pathological processes in every tissue in the body. The brain is composed of a highly complex milieu of different cell types and few methods exist that can identify which individual cells in a complex mixture are secreting specific analytes. By identifying which cells are responsible, we can better understand neural physiology and pathophysiology, more readily identify the underlying pathways responsible for analyte production, and ultimately use this information to guide the development of novel therapeutic strategies that target the cell types of relevance. We present here a method for detecting analytes secreted from single human induced pluripotent stem cell (iPSC)-derived neural cells and have applied the method to measure amyloid β (Aβ) and soluble amyloid precursor protein-alpha (sAPPα), analytes central to Alzheimer's disease pathogenesis. Through these studies, we have uncovered the dynamic range of secretion profiles of these analytes from single iPSC-derived neuronal and glial cells and have molecularly characterized subpopulations of these cells through immunostaining and gene expression analyses. In examining Aβ and sAPPα secretion from single cells, we were able to identify previously unappreciated complexities in the biology of APP cleavage that could not otherwise have been found by studying averaged responses over pools of cells. This technique can be readily adapted to the detection of other analytes secreted by neural cells, which would have the potential to open new perspectives into human CNS development and dysfunction.W. M. Keck FoundationNational Institute of Mental Health (U.S.) (R21MH096233)National Institute on Aging (R33AG049864)National Cancer Institute (U.S.) (P30-CA14051

Distinct Effects on Diversifying Selection by Two Mechanisms of Immunity Against Streptococcus pneumoniae

Antigenic variation to evade host immunity has long been assumed to be a driving force of diversifying selection in pathogens. Colonization by Streptococcus pneumoniae, which is central to the organism's transmission and therefore evolution, is limited by two arms of the immune system: antibody- and T cell- mediated immunity. In particular, the effector activity of CD4+ TH17 cell mediated immunity has been shown to act in trans, clearing co-colonizing pneumococci that do not bear the relevant antigen. It is thus unclear whether TH17 cell immunity allows benefit of antigenic variation and contributes to diversifying selection. Here we show that antigen-specific CD4+ TH17 cell immunity almost equally reduces colonization by both an antigen-positive strain and a co-colonized, antigen-negative strain in a mouse model of pneumococcal carriage, thus potentially minimizing the advantage of escape from this type of immunity. Using a proteomic screening approach, we identified a list of candidate human CD4+ TH17 cell antigens. Using this list and a previously published list of pneumococcal Antibody antigens, we bioinformatically assessed the signals of diversifying selection among the identified antigens compared to non-antigens. We found that Antibody antigen genes were significantly more likely to be under diversifying selection than the TH17 cell antigen genes, which were indistinguishable from non-antigens. Within the Antibody antigens, epitopes recognized by human antibodies showed stronger evidence of diversifying selection. Taken together, the data suggest that TH17 cell-mediated immunity, one form of T cell immunity that is important to limit carriage of antigen-positive pneumococcus, favors little diversifying selection in the targeted antigen. The results could provide new insight into pneumococcal vaccine design

Two Vaccines for Staphylococcus aureus Induce a B-Cell- Mediated Immune Response

Staphylococcus aureus causes severe disease in humans for which no licensed vaccine exists. A novel S. aureus vaccine (SA4Ag) is in development, targeting the capsular polysaccharides (CPs) and two virulence-associated surface proteins. Vaccine-elicited antibody responses to CPs are efficacious against serious infection by other encapsulated bacteria. Studies of natural S. aureus infection have also shown a role for TH17 and/or TH1 responses in protection. Single-antigen vaccines, including CPs, have not been effective against S. aureus; a multiantigen vaccine approach is likely required. However, the impact of addition of protein antigens on the immune response to CPs has not been studied. Here, the immune response induced by a bivalent CP conjugate vaccine (to model the established mechanism of action of vaccine-induced protection against Gram-positive pathogens) was compared to the response induced by SA4Ag, which contains both CP conjugates and protein antigens, in cynomolgus macaques. Microengraving, flow cytometry, opsonophagocytic assays, and Luminex technology were used to analyze the B-cell, T-cell, functional antibody, and innate immune responses. Both the bivalent CP vaccine and SA4Ag induced cytokine production from naive cells and antigen-specific memory B-cell and functional antibody responses. Increases in levels of circulating, activated T cells were not apparent following vaccination, nor was a TH17 or TH1 response evident. However, our data are consistent with a vaccine-induced recruitment of T follicular helper (TFH) cells to lymph nodes. Collectively, these data suggest that the response to SA4Ag is primarily mediated by B cells and antibodies that abrogate important S. aureus virulence mechanisms.IMPORTANCEStaphylococcus aureus causes severe disease in humans for which no licensed vaccine exists. A novel vaccine is in development that targets multiple elements of the bacteria since single-component vaccines have not shown efficacy to date. How these multiple components alter the immune response raised by the vaccine is not well studied. We found that the addition of two protein components did not alter substantially the antibody responses raised with respect to function or mobilization of B cells. There was also not a substantial change in the activity of T cells, another part of the adaptive response. This study showed that protection by this vaccine may be mediated primarily by antibody protection.Pfizer Inc.National Cancer Institute (U.S.) (grant P30-CA14051

Treatment with stem cells in orthopaedic surgery

Stem cells are multipotent cells exerting anti-inflammatory and immunomodulatory effects. Mesenchymal stem cells are the most well-known and used stem cells in orthopaedic surgery. In this review, we provide an overview of the current local use of stem cells in the treatment of osteoarthritis, bone defects, tendinopathy, and rotator cuff lesions. Conclusively, the future use of stem cells in orthopaedic treatments seems to have potential regarding not only pain relief, but also the possible curative effect of certain conditions

Treatment with stem cells in orthopaedic surgery

Stem cells are multipotent cells exerting anti-inflammatory and immunomodulatory effects. Mesenchymal stem cells are the most well-known and used stem cells in orthopaedic surgery. In this review, we provide an overview of the current local use of stem cells in the treatment of osteoarthritis, bone defects, tendinopathy, and rotator cuff lesions. Conclusively, the future use of stem cells in orthopaedic treatments seems to have potential regarding not only pain relief, but also the possible curative effect of certain conditions

Treatment with stem cells in orthopaedic surgery

Stem cells are multipotent cells exerting anti-inflammatory and immunomodulatory effects. Mesenchymal stem cells are the most well-known and used stem cells in orthopaedic surgery. In this review, we provide an overview of the current local use of stem cells in the treatment of osteoarthritis, bone defects, tendinopathy, and rotator cuff lesions. Conclusively, the future use of stem cells in orthopaedic treatments seems to have potential regarding not only pain relief, but also the possible curative effect of certain conditions

Seq-Well: A Portable, Low-Cost Platform for High-Throughput Single-Cell RNA-Seq of Low-Input Samples

Single-cell RNA-Seq can precisely resolve cellular states but application to sparse samples is challenging. Here, we present Seq-Well, a portable, low-cost platform for massively-parallel single-cell RNA-Seq. Barcoded mRNA capture beads and single cells are sealed in an array of subnanoliter wells using a semi-permeable membrane, enabling efficient cell lysis and transcript capture. We characterize Seq-Well using species-mixing experiments and PBMCs, and profile thousands of primary human macrophages exposed to tuberculosis

Multimodal profiling of lung granulomas in macaques reveals cellular correlates of tuberculosis control

Mycobacterium tuberculosis lung infection results in a complex multicellular structure: the granuloma. In some granulomas, immune activity promotes bacterial clearance, but in others, bacteria persist and grow. We identified correlates of bacterial control in cynomolgus macaque lung granulomas by co-registering longitudinal positron emission tomography and computed tomography imaging, single-cell RNA sequencing, and measures of bacterial clearance. Bacterial persistence occurred in granulomas enriched for mast, endothelial, fibroblast, and plasma cells, signaling amongst themselves via type 2 immunity and wound-healing pathways. Granulomas that drove bacterial control were characterized by cellular ecosystems enriched for type 1-type 17, stem-like, and cytotoxic T cells engaged in pro-inflammatory signaling networks involving diverse cell populations. Granulomas that arose later in infection displayed functional characteristics of restrictive granulomas and were more capable of killing Mtb. Our results define the complex multicellular ecosystems underlying (lack of) granuloma resolution and highlight host immune targets that can be leveraged to develop new vaccine and therapeutic strategies for TB

A practical guide to single-cell RNA-sequencing for biomedical research and clinical applications.

RNA sequencing (RNA-seq) is a genomic approach for the detection and quantitative analysis of messenger RNA molecules in a biological sample and is useful for studying cellular responses. RNA-seq has fueled much discovery and innovation in medicine over recent years. For practical reasons, the technique is usually conducted on samples comprising thousands to millions of cells. However, this has hindered direct assessment of the fundamental unit of biology-the cell. Since the first single-cell RNA-sequencing (scRNA-seq) study was published in 2009, many more have been conducted, mostly by specialist laboratories with unique skills in wet-lab single-cell genomics, bioinformatics, and computation. However, with the increasing commercial availability of scRNA-seq platforms, and the rapid ongoing maturation of bioinformatics approaches, a point has been reached where any biomedical researcher or clinician can use scRNA-seq to make exciting discoveries. In this review, we present a practical guide to help researchers design their first scRNA-seq studies, including introductory information on experimental hardware, protocol choice, quality control, data analysis and biological interpretation