ENGINEERING PROTEINS WITH UNIQUE CHARACTERISTICS FOR DIAGNOSTICS AND BIOSENSORS

Proteins possess a broad range of structural and functional properties and, therefore, can be employed in a variety of biomedical applications. While a good number of protein-based biosensing systems and biosensors for target analytes have been developed, the search for versatile, highly sensitive and selective sensors with long term stability able to provide fast detection of target analytes continues to be a challenge. To that end, we now report the design and development of modified proteins with tailored characteristics and their further utilization in the development of biosensing systems. We take advantage of binding proteins that undergo a change in conformation upon binding to their respective target ligand analytes for the development of highly selective biosensing systems. The first class of binding proteins that was explored for this purpose was antibodies. A non-canonical site in the variable region of a monoclonal antibody was tagged with a fluorescent probe to sense the binding of analyte to its corresponding antigen-binding site. The strategy employed for designing antibodysensing molecules is universal as it can be employed for sensing any biomolecule of interest provided that there is an available antibody against the target ligand analyte. In a second strategy, we utilized designer glucose recognition proteins (GRPs) that were prepared by incorporation of unnatural amino acids in the glucose/galactose binding protein (GBP) of Escherichia coli and its truncated fragments. By taking advantage of the global incorporation method, we were able to fine-tune the binding affinity and thermal stability of the proteins, thus, allowing for the development of a reagentless fluorescence based fiber optic glucose biosensor capable of monitoring glucose in the hypoglycemic, normal, and hyperglycemic range, as well as in the hypothermic and hyperthermic temperature range

Cell-to-Cell Transfer of M. tuberculosis Antigens Optimizes CD4 T Cell Priming

SummaryDuring Mycobacterium tuberculosis and other respiratory infections, optimal T cell activation requires pathogen transport from the lung to a local draining lymph node (LN). However, the infected inflammatory monocyte-derived dendritic cells (DCs) that transport M. tuberculosis to the local lymph node are relatively inefficient at activating CD4 T cells, possibly due to bacterial inhibition of antigen presentation. We found that infected migratory DCs release M. tuberculosis antigens as soluble, unprocessed proteins for uptake and presentation by uninfected resident lymph node DCs. This transfer of bacterial proteins from migratory to local DCs results in optimal priming of antigen-specific CD4 T cells, which are essential in controlling tuberculosis. Additionally, this mechanism does not involve transfer of the whole bacterium and is distinct from apoptosis or exosome shedding. These findings reveal a mechanism that bypasses pathogen inhibition of antigen presentation by infected cells and generates CD4 T cell responses that control the infection

Polypeptides, Systems, and Methods Useful for Detecting Glucose

The presently-disclosed subject matter provides biosensors for detecting molecules of interest. The biosensors include a polypeptide capable of selectively-binding glucose, wherein the polypeptide molecule is selected from: an unnatural analogue of wild type glucose binding protein; a fragment of wild type glucose binding protein; and an unnatural analogue fragment of wild type glucose binding protein

Red-Shifted Aequorin Variants Incorporating Non-Canonical Amino Acids: Applications in \u3cem\u3eIn Vivo\u3c/em\u3e Imaging

The increased importance of in vivo diagnostics has posed new demands for imaging technologies. In that regard, there is a need for imaging molecules capable of expanding the applications of current state-of-the-art imaging in vivo diagnostics. To that end, there is a desire for new reporter molecules capable of providing strong signals, are non-toxic, and can be tailored to diagnose or monitor the progression of a number of diseases. Aequorin is a non-toxic photoprotein that can be used as a sensitive marker for bioluminescence in vivo imaging. The sensitivity of aequorin is due to the fact that bioluminescence is a rare phenomenon in nature and, therefore, it does not suffer from autofluorescence, which contributes to background emission. Emission of bioluminescence in the blue-region of the spectrum by aequorin only occurs when calcium, and its luciferin coelenterazine, are bound to the protein and trigger a biochemical reaction that results in light generation. It is this reaction that endows aequorin with unique characteristics, making it ideally suited for a number of applications in bioanalysis and imaging. Herein we report the site-specific incorporation of non-canonical or non-natural amino acids and several coelenterazine analogues, resulting in a catalog of 72 cysteine-free, aequorin variants which expand the potential applications of these photoproteins by providing several red-shifted mutants better suited to use in vivo. In vivo studies in mouse models using the transparent tissue of the eye confirmed the activity of the aequorin variants incorporating L-4-iodophehylalanine and L-4-methoxyphenylalanine after injection into the eye and topical addition of coelenterazine. The signal also remained localized within the eye. This is the first time that aequorin variants incorporating non-canonical amino acids have shown to be active in vivo and useful as reporters in bioluminescence imaging

Immunophenotyping and Transcriptomic Outcomes in PDX-Derived TNBC Tissue

Cancer tissue functions as an ecosystem of a diverse set of cells that interact in a complex tumor microenvironment (TME). Genomic tools applied to biopsies in bulk fail to account for this tumor heterogeneity while single cell imaging methods limit the number of cells which can be assessed or are very resource intensive. The current study presents methods based on flow cytometric analysis and cell sorting using known cell surface markers (eg, CD184, CD24, CD90) to identify and interrogate distinct groups of cells in triple-negative breast cancer (TNBC) clinical biopsy specimens from patient-derived xenograft (PDX) models. The results demonstrate that flow cytometric analysis allows a relevant subgrouping of cancer tissue and that sorting of these subgroups provides insights on cancer cell populations with unique, reproducible and functionally divergent gene expression profiles. The discovery of a drug resistance signature implies that uncovering the functional interaction between these populations will lead to deeper understanding of cancer progression and drug response. Implications: PDX-derived human breast cancer tissue was investigated at the single cell level and cell subpopulations defined by surface markers were identified which suggest specific roles for distinct cellular compartments within a solid tumor

Association of genetic variation with systolic and diastolic blood pressure among African Americans: the Candidate Gene Association Resource study

The prevalence of hypertension in African Americans (AAs) is higher than in other US groups; yet, few have performed genome-wide association studies (GWASs) in AA. Among people of European descent, GWASs have identified genetic variants at 13 loci that are associated with blood pressure. It is unknown if these variants confer susceptibility in people of African ancestry. Here, we examined genome-wide and candidate gene associations with systolic blood pressure (SBP) and diastolic blood pressure (DBP) using the Candidate Gene Association Resource (CARe) consortium consisting of 8591 AAs. Genotypes included genome-wide single-nucleotide polymorphism (SNP) data utilizing the Affymetrix 6.0 array with imputation to 2.5 million HapMap SNPs and candidate gene SNP data utilizing a 50K cardiovascular gene-centric array (ITMAT-Broad-CARe [IBC] array). For Affymetrix data, the strongest signal for DBP was rs10474346 (P= 3.6 × 10−8) located near GPR98 and ARRDC3. For SBP, the strongest signal was rs2258119 in C21orf91 (P= 4.7 × 10−8). The top IBC association for SBP was rs2012318 (P= 6.4 × 10−6) near SLC25A42 and for DBP was rs2523586 (P= 1.3 × 10−6) near HLA-B. None of the top variants replicated in additional AA (n = 11 882) or European-American (n = 69 899) cohorts. We replicated previously reported European-American blood pressure SNPs in our AA samples (SH2B3, P= 0.009; TBX3-TBX5, P= 0.03; and CSK-ULK3, P= 0.0004). These genetic loci represent the best evidence of genetic influences on SBP and DBP in AAs to date. More broadly, this work supports that notion that blood pressure among AAs is a trait with genetic underpinnings but also with significant complexit

Mapping 123 million neonatal, infant and child deaths between 2000 and 2017

Since 2000, many countries have achieved considerable success in improving child survival, but localized progress remains unclear. To inform efforts towards United Nations Sustainable Development Goal 3.2—to end preventable child deaths by 2030—we need consistently estimated data at the subnational level regarding child mortality rates and trends. Here we quantified, for the period 2000–2017, the subnational variation in mortality rates and number of deaths of neonates, infants and children under 5 years of age within 99 low- and middle-income countries using a geostatistical survival model. We estimated that 32% of children under 5 in these countries lived in districts that had attained rates of 25 or fewer child deaths per 1,000 live births by 2017, and that 58% of child deaths between 2000 and 2017 in these countries could have been averted in the absence of geographical inequality. This study enables the identification of high-mortality clusters, patterns of progress and geographical inequalities to inform appropriate investments and implementations that will help to improve the health of all populations

Association of genetic variation with systolic and diastolic blood pressure among African Americans: the Candidate Gene Association Resource study.

The prevalence of hypertension in African Americans (AAs) is higher than in other US groups; yet, few have performed genome-wide association studies (GWASs) in AA. Among people of European descent, GWASs have identified genetic variants at 13 loci that are associated with blood pressure. It is unknown if these variants confer susceptibility in people of African ancestry. Here, we examined genome-wide and candidate gene associations with systolic blood pressure (SBP) and diastolic blood pressure (DBP) using the Candidate Gene Association Resource (CARe) consortium consisting of 8591 AAs. Genotypes included genome-wide single-nucleotide polymorphism (SNP) data utilizing the Affymetrix 6.0 array with imputation to 2.5 million HapMap SNPs and candidate gene SNP data utilizing a 50K cardiovascular gene-centric array (ITMAT-Broad-CARe [IBC] array). For Affymetrix data, the strongest signal for DBP was rs10474346 (P= 3.6 × 10(-8)) located near GPR98 and ARRDC3. For SBP, the strongest signal was rs2258119 in C21orf91 (P= 4.7 × 10(-8)). The top IBC association for SBP was rs2012318 (P= 6.4 × 10(-6)) near SLC25A42 and for DBP was rs2523586 (P= 1.3 × 10(-6)) near HLA-B. None of the top variants replicated in additional AA (n = 11 882) or European-American (n = 69 899) cohorts. We replicated previously reported European-American blood pressure SNPs in our AA samples (SH2B3, P= 0.009; TBX3-TBX5, P= 0.03; and CSK-ULK3, P= 0.0004). These genetic loci represent the best evidence of genetic influences on SBP and DBP in AAs to date. More broadly, this work supports that notion that blood pressure among AAs is a trait with genetic underpinnings but also with significant complexity

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms