Genome of the Avirulent Human-Infective Trypanosome—Trypanosoma rangeli

Background: Trypanosoma rangeli is a hemoflagellate protozoan parasite infecting humans and other wild and domestic mammals across Central and South America. It does not cause human disease, but it can be mistaken for the etiologic agent of Chagas disease, Trypanosoma cruzi. We have sequenced the T. rangeli genome to provide new tools for elucidating the distinct and intriguing biology of this species and the key pathways related to interaction with its arthropod and mammalian hosts.  Methodology/Principal Findings: The T. rangeli haploid genome is ,24 Mb in length, and is the smallest and least repetitive trypanosomatid genome sequenced thus far. This parasite genome has shorter subtelomeric sequences compared to those of T. cruzi and T. brucei; displays intraspecific karyotype variability and lacks minichromosomes. Of the predicted 7,613 protein coding sequences, functional annotations could be determined for 2,415, while 5,043 are hypothetical proteins, some with evidence of protein expression. 7,101 genes (93%) are shared with other trypanosomatids that infect humans. An ortholog of the dcl2 gene involved in the T. brucei RNAi pathway was found in T. rangeli, but the RNAi machinery is non-functional since the other genes in this pathway are pseudogenized. T. rangeli is highly susceptible to oxidative stress, a phenotype that may be explained by a smaller number of anti-oxidant defense enzymes and heatshock proteins.  Conclusions/Significance: Phylogenetic comparison of nuclear and mitochondrial genes indicates that T. rangeli and T. cruzi are equidistant from T. brucei. In addition to revealing new aspects of trypanosome co-evolution within the vertebrate and invertebrate hosts, comparative genomic analysis with pathogenic trypanosomatids provides valuable new information that can be further explored with the aim of developing better diagnostic tools and/or therapeutic targets

Identification of a wide spectrum of ciliary gene mutations in nonsyndromic biliary atresia patients implicates ciliary dysfunction as a novel disease mechanism

Background: Biliary atresia (BA) is the most common obstructive cholangiopathy in neonates, often progressing to end-stage cirrhosis. BA pathogenesis is believed to be multifactorial, but the genetic contribution, especially for nonsyndromic BA (common form: > 85%) remains poorly defined. Methods: We conducted whole exome sequencing on 89 nonsyndromic BA trios to identify rare variants contributing to BA etiology. Functional evaluation using patients’ liver biopsies, human cell and zebrafish models were performed. Clinical impact on respiratory system was assessed with clinical evaluation, nasal nitric oxide (nNO), high speed video analysis and transmission electron microscopy. Findings: We detected rare, deleterious de novo or biallelic variants in liver-expressed ciliary genes in 31.5% (28/89) of the BA patients. Burden test revealed 2.6-fold (odds ratio (OR) [95% confidence intervals (CI)]= 2.58 [1.15–6.07], adjusted p = 0.034) over-representation of rare, deleterious mutations in liver-expressed ciliary gene set in patients compared to controls. Functional analyses further demonstrated absence of cilia in the BA livers with KIF3B and TTC17 mutations, and knockdown of PCNT, KIF3B and TTC17 in human control fibroblasts and cholangiocytes resulted in reduced number of cilia. Additionally, CRISPR/Cas9-engineered zebrafish knockouts of KIF3B, PCNT and TTC17 displayed reduced biliary flow. Abnormally low level of nNO was detected in 80% (8/10) of BA patients carrying deleterious ciliary mutations, implicating the intrinsic ciliary defects. Interpretation: Our findings support strong genetic susceptibility for nonsyndromic BA. Ciliary gene mutations leading to cholangiocyte cilia malformation and dysfunction could be a key biological mechanism in BA pathogenesis. Funding: The study is supported by General Research Fund, HMRF Commissioned Paediatric Research at HKCH and Li Ka Shing Faculty of Medicine Enhanced New Staff Start-up Fund

Predictors of glycemic control among patients with Type 2 diabetes: A longitudinal study

BACKGROUND: Diabetes is the sixth leading cause of death and results in significant morbidity. The purpose of this study is to determine what demographic, health status, treatment, access/quality of care, and behavioral factors are associated with poor glycemic control in a Type 2 diabetic, low-income, minority, San Diego population. METHODS: Longitudinal observational data was collected on patients with Type 2 diabetes from Project Dulce, a program in San Diego County designed to care for an underserved diabetic population. The study sample included 573 patients with a racial/ethnic mix of 53% Hispanic, 7% black, 18% Asian, 20% white, and 2% other. We utilized mixed effects models to determine the factors associated with poor glycemic control using hemoglobin A1C (A1C) as the outcome of interest. A multi-step model building process was used resulting in a final parsimonious model with main effects and interaction terms. RESULTS: Patients had a mean age of 55 years, 69% were female, the mean duration of diabetes was 7.1 years, 31% were treated with insulin, and 57% were obese. American Diabetes Association (ADA) recommendations for blood pressure and total cholesterol were met by 71% and 68%, respectively. Results of the mixed effects model showed that patients who were uninsured, had diabetes for a longer period of time, used insulin or multiple oral agents, or had high cholesterol had higher A1C values over time indicating poorer glycemic control. The younger subjects also had poorer control. CONCLUSION: This study provides factors that predict glycemic control in a specific low-income, multiethnic, Type 2 diabetic population. With this information, subgroups with high risk of disease morbidity were identified. Barriers that prevent these patients from meeting their goals must be explored to improve health outcomes

Identification of the risk for liver fibrosis on CHB patients using an artificial neural network based on routine and serum markers

<p>Abstract</p> <p>Background</p> <p>Liver fibrosis progression is commonly found in patients with CHB. Liver biopsy is a gold standard for identifying the extent of liver fibrosis, but has many draw-backs. It is essential to construct a noninvasive model to predict the levels of risk for liver fibrosis. It would provide very useful information to help reduce the number of liver biopsies of CHB patients.</p> <p>Methods</p> <p>339 chronic hepatitis B patients with HBsAg-positive were investigated retrospectively, and divided at random into 2 subsets with twice as many patients in the training set as in the validation set; 116 additional patients were consequently enrolled in the study as the testing set. A three-layer artificial neural network was developed using a Bayesian learning algorithm. Sensitivity and ROC analysis were performed to explain the importance of input variables and the performance of the neural network.</p> <p>Results</p> <p>There were 329 patients without significant fibrosis and 126 with significant fibrosis in the study. All markers except gender, HB, ALP and TP were found to be statistically significant factors associated with significant fibrosis. The sensitivity analysis showed that the most important factors in the predictive model were age, AST, platelet, and GGT, and the influence on the output variable among coal miners were 22.3-24.6%. The AUROC in 3 sets was 0.883, 0.884, and 0.920. In the testing set, for a decision threshold of 0.33, sensitivity and negative predictive values were 100% and all CHB patients with significant fibrosis would be identified.</p> <p>Conclusions</p> <p>The artificial neural network model based on routine and serum markers would predict the risk for liver fibrosis with a high accuracy. 47.4% of CHB patients at a decision threshold of 0.33 would be free of liver biopsy and wouldn't be missed.</p

Comparative Genomics Reveals Two Novel RNAi Factors in Trypanosoma brucei and Provides Insight into the Core Machinery

The introduction ten years ago of RNA interference (RNAi) as a tool for molecular exploration in Trypanosoma brucei has led to a surge in our understanding of the pathogenesis and biology of this human parasite. In particular, a genome-wide RNAi screen has recently been combined with next-generation Illumina sequencing to expose catalogues of genes associated with loss of fitness in distinct developmental stages. At present, this technology is restricted to RNAi-positive protozoan parasites, which excludes T. cruzi, Leishmania major, and Plasmodium falciparum. Therefore, elucidating the mechanism of RNAi and identifying the essential components of the pathway is fundamental for improving RNAi efficiency in T. brucei and for transferring the RNAi tool to RNAi-deficient pathogens. Here we used comparative genomics of RNAi-positive and -negative trypanosomatid protozoans to identify the repertoire of factors in T. brucei. In addition to the previously characterized Argonaute 1 (AGO1) protein and the cytoplasmic and nuclear Dicers, TbDCL1 and TbDCL2, respectively, we identified the RNA Interference Factors 4 and 5 (TbRIF4 and TbRIF5). TbRIF4 is a 3′-5′ exonuclease of the DnaQ superfamily and plays a critical role in the conversion of duplex siRNAs to the single-stranded form, thus generating a TbAGO1-siRNA complex required for target-specific cleavage. TbRIF5 is essential for cytoplasmic RNAi and appears to act as a TbDCL1 cofactor. The availability of the core RNAi machinery in T. brucei provides a platform to gain mechanistic insights in this ancient eukaryote and to identify the minimal set of components required to reconstitute RNAi in RNAi-deficient parasites

Aging and Visual Counting

Much previous work on how normal aging affects visual enumeration has been focused on the response time required to enumerate, with unlimited stimulus duration. There is a fundamental question, not yet addressed, of how many visual items the aging visual system can enumerate in a "single glance", without the confounding influence of eye movements.We recruited 104 observers with normal vision across the age span (age 21-85). They were briefly (200 ms) presented with a number of well- separated black dots against a gray background on a monitor screen, and were asked to judge the number of dots. By limiting the stimulus presentation time, we can determine the maximum number of visual items an observer can correctly enumerate at a criterion level of performance (counting threshold, defined as the number of visual items at which ≈63% correct rate on a psychometric curve), without confounding by eye movements. Our findings reveal a 30% decrease in the mean counting threshold of the oldest group (age 61-85: ∼5 dots) when compared with the youngest groups (age 21-40: 7 dots). Surprisingly, despite decreased counting threshold, on average counting accuracy function (defined as the mean number of dots reported for each number tested) is largely unaffected by age, reflecting that the threshold loss can be primarily attributed to increased random errors. We further expanded this interesting finding to show that both young and old adults tend to over-count small numbers, but older observers over-count more.Here we show that age reduces the ability to correctly enumerate in a glance, but the accuracy (veridicality), on average, remains unchanged with advancing age. Control experiments indicate that the degraded performance cannot be explained by optical, retinal or other perceptual factors, but is cortical in origin

A Network-Based Multi-Target Computational Estimation Scheme for Anticoagulant Activities of Compounds

BACKGROUND: Traditional virtual screening method pays more attention on predicted binding affinity between drug molecule and target related to a certain disease instead of phenotypic data of drug molecule against disease system, as is often less effective on discovery of the drug which is used to treat many types of complex diseases. Virtual screening against a complex disease by general network estimation has become feasible with the development of network biology and system biology. More effective methods of computational estimation for the whole efficacy of a compound in a complex disease system are needed, given the distinct weightiness of the different target in a biological process and the standpoint that partial inhibition of several targets can be more efficient than the complete inhibition of a single target. METHODOLOGY: We developed a novel approach by integrating the affinity predictions from multi-target docking studies with biological network efficiency analysis to estimate the anticoagulant activities of compounds. From results of network efficiency calculation for human clotting cascade, factor Xa and thrombin were identified as the two most fragile enzymes, while the catalytic reaction mediated by complex IXa:VIIIa and the formation of the complex VIIIa:IXa were recognized as the two most fragile biological matter in the human clotting cascade system. Furthermore, the method which combined network efficiency with molecular docking scores was applied to estimate the anticoagulant activities of a serial of argatroban intermediates and eight natural products respectively. The better correlation (r = 0.671) between the experimental data and the decrease of the network deficiency suggests that the approach could be a promising computational systems biology tool to aid identification of anticoagulant activities of compounds in drug discovery. CONCLUSIONS: This article proposes a network-based multi-target computational estimation method for anticoagulant activities of compounds by combining network efficiency analysis with scoring function from molecular docking

Stromal cells in tertiary lymphoid structures:Architects of autoimmunity

The molecular mediators present within the inflammatory microenvironment are able, in certain conditions, to favor the initiation of tertiary lymphoid structure (TLS) development. TLS is organized lymphocyte clusters able to support antigen-specific immune response in non-immune organs. Importantly, chronic inflammation does not always result in TLS formation; instead, TLS has been observed to develop specifically in permissive organs, suggesting the presence of tissue-specific cues that are able to imprint the immune responses and form TLS hubs. Fibroblasts are tissue-resident cells that define the anatomy and function of a specific tissue. Fibroblast plasticity and specialization in inflammatory conditions have recently been unraveled in both immune and non-immune organs revealing a critical role for these structural cells in human physiology. Here, we describe the role of fibroblasts in the context of TLS formation and its functional maintenance in the tissue, highlighting their potential role as therapeutic disease targets in TLS-associated diseases.</p

The Concise Guide to PHARMACOLOGY 2023/24: G protein-coupled receptors.

The Concise Guide to PHARMACOLOGY 2023/24 is the sixth in this series of biennial publications. The Concise Guide provides concise overviews, mostly in tabular format, of the key properties of approximately 1800 drug targets, and about 6000 interactions with about 3900 ligands. There is an emphasis on selective pharmacology (where available), plus links to the open access knowledgebase source of drug targets and their ligands (https://www.guidetopharmacology.org), which provides more detailed views of target and ligand properties. Although the Concise Guide constitutes almost 500 pages, the material presented is substantially reduced compared to information and links presented on the website. It provides a permanent, citable, point-in-time record that will survive database updates. The full contents of this section can be found at http://onlinelibrary.wiley.com/doi/bph.16177. G protein-coupled receptors are one of the six major pharmacological targets into which the Guide is divided, with the others being: ion channels, nuclear hormone receptors, catalytic receptors, enzymes and transporters. These are presented with nomenclature guidance and summary information on the best available pharmacological tools, alongside key references and suggestions for further reading. The landscape format of the Concise Guide is designed to facilitate comparison of related targets from material contemporary to mid-2023, and supersedes data presented in the 2021/22, 2019/20, 2017/18, 2015/16 and 2013/14 Concise Guides and previous Guides to Receptors and Channels. It is produced in close conjunction with the Nomenclature and Standards Committee of the International Union of Basic and Clinical Pharmacology (NC-IUPHAR), therefore, providing official IUPHAR classification and nomenclature for human drug targets, where appropriate