Kloniranje, ekspresija i karakterizacija paraflagelarnog gena Rod 2 bičaša Trypanosoma evansi

Paraflagellar rod is the major structural component of the trypanosomatid flagellum and is identified as a complex lattice of filaments which runs parallel to the axoneme throughout most of the flagellar length. The present study was carried out to investigate the existence of the paraflagellar rod (PFR 2) gene in Trypanosoma evansi infecting Indian cattle. Local isolates of T. evansi collected from naturally infected cow were multiplied in Wistar rats. Complementary DNA (cDNA) was synthesized from the RNA of host cell free T. evansi parasites by reverse transcription. The gel purified PCR product (PFR 2 gene of T. evansi) was cloned into the pTZ57R/T vector system. The nucleotide sequence of the PFR 2 gene of the T. evansi S.V.V.U. isolate (Accession No. KT277497) obtained in the present study revealed 100% homology with T. evansi China isolate and 99% homology with T. evansi Izatnagar and Bikaner isolates. The recombinant protein was sub-cloned into pET 32a and expressed in the BL21 (DE3) pLysS expression system. The PFR 2 gene of T. evansi S.V.V.U. isolate was further characterized by determination of its protein profile with SDS-PAGE and western blotting. Indirect ELISA was optimized for detection of the specific antibody titre against the recombinant protein of the PFR 2 gene of T. evansi. In the kinetoplastid species the PFR 2 gene is highly conserved. Therefore the PFR 2 gene was suggested as a vaccine candidate, as well as a diagnostic antigen.Paraflagelarni štapić glavna je strukturna komponenta tripanosomskog biča i dio je kompleksa filamenaza koji teku paralelno s aksonemom duž biča. Istraživanje je provedeno kako bi se ispitalo postojanje paraflagelarnog gena Rod 2 (PFR2) u bičaša Trypanosoma evansi koji invadira goveda u Indiji. Lokalni izolat T. evansi prikupljen od prirodno invadiranih krava umnožen je u Wistar štakora. Komplementarna DNA (cDNA) sintetizirana je iz RNA obrnutom transkripcijom iz stanica neinvadiranih nositelja T. evansi parazita. Pročišćeni PCR produkt (gen PFR2 bičaša T. evansi) kloniran je u vektorski sustav pTZ57R/T. Nukleotidna sekvencija gena PFR2 bičaša T. evansi, izolat S.V.V.U. (pristupni broj KT277497) dobivena u ovom istraživanju pokazala je 100 %-tnu sličnost s izolatom T. evansi China i 99 %-tnu s izolatom T. evansi Izatnagar i Bikaner. Rekombinantni protein ponovno je kloniran u sustavu pET 32a i prikazan u sustavu BL21 (DE3) pLysS. Gen PFR2 bičaša T. evansi, izolat S.V.V.U. dalje je karakteriziran određivanjem proteinskog profila metodama SDS-PAGE i Western blotting. Indirektni test ELISA optimiziran je za dokaz titra specifičnih protutijela za rekombinantni protein gena PFR2 bičaša T. evansi. U kinetoplastida gen PFR2 izrazito je očuvan. Stoga bi se gen PFR2 mogao upotrijebiti za cjepivo te kao dijagnostički antigen

Developing proso millet (Panicum miliaceum L.) core collection using geographic and morpho-agronomic data

Proso millet (Panicum miliaceum L.) is a rich source of protein, minerals, and vitamins, and is an important cereal crop of Asia and Africa. Due to its lowest water and nutrient requirement, it has the potential for agriculture diversification. The development of a core collection would assist in efficient management and enhanced utilisation of proso millet genetic resources. The present investigation was conducted to develop a core collection of proso millet based on geographic information and 20 qualitative and quantitative traits recorded on 833 accessions conserved in the International Crops Research Institute for the Semi-Arid Tropics genebank. The entire germplasm collection was stratified into five groups based on races and data on 20 morpho-agronomic traits were used for clustering following Ward’s method. About 10% (or at least one accession) was randomly selected from each of 101 clusters to constitute a core collection of 106 accessions. Comparisons of means, variances, frequency distribution, diversity indices, and correlation studies indicated that the variation in the entire collection has been preserved in the core collection. This core collection provides a gateway to identify diverse trait-specific germplasm accessions for important agronomic traits and for abiotic and biotic stresses for use in crop improvement research and in crop diversification programs

Genomic regions associated with resistance to peanut bud necrosis disease (PBND) in a recombinant inbred line (RIL) population

Parents and 318 F8 recombinant inbred lines (RILs) derived from the cross, TAG 24 × ICGV 86031 were evaluated for peanut bud necrosis disease (PBND) resistance and agronomic traits under natural infestation of thrips at a disease hotspot location for 2 years. Significant genotype, environment and genotype × environment interaction effects suggested role of environment in development and spread of the disease. Quantitative trait loci (QTL) analysis using QTL Cartographer identified a total of 14 QTL for six traits of which five QTL were for disease incidence. One quantitative trait locus q60DI located on LG_AhII was identified using both QTL Cartographer and QTL Network. Another QTL q90DI was detected with a high PVE of 12.57 using QTL Cartographer. A total of nine significant additive × additive (AA) interactions were detected for PBND disease incidence and yield traits with two and seven interactions displaying effects in favour of the parental and recombinant genotype combinations, respectively. This is the first attempt on QTL discovery associated with PBND resistance in peanut. Superior RILs identified in the study can be recycled or released as variety following further evaluations

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Genetic mechanisms of critical illness in COVID-19.

Host-mediated lung inflammation is present1, and drives mortality2, in the critical illness caused by coronavirus disease 2019 (COVID-19). Host genetic variants associated with critical illness may identify mechanistic targets for therapeutic development3. Here we report the results of the GenOMICC (Genetics Of Mortality In Critical Care) genome-wide association study in 2,244 critically ill patients with COVID-19 from 208 UK intensive care units. We have identified and replicated the following new genome-wide significant associations: on chromosome 12q24.13 (rs10735079, P = 1.65 × 10-8) in a gene cluster that encodes antiviral restriction enzyme activators (OAS1, OAS2 and OAS3); on chromosome 19p13.2 (rs74956615, P = 2.3 × 10-8) near the gene that encodes tyrosine kinase 2 (TYK2); on chromosome 19p13.3 (rs2109069, P = 3.98 ×  10-12) within the gene that encodes dipeptidyl peptidase 9 (DPP9); and on chromosome 21q22.1 (rs2236757, P = 4.99 × 10-8) in the interferon receptor gene IFNAR2. We identified potential targets for repurposing of licensed medications: using Mendelian randomization, we found evidence that low expression of IFNAR2, or high expression of TYK2, are associated with life-threatening disease; and transcriptome-wide association in lung tissue revealed that high expression of the monocyte-macrophage chemotactic receptor CCR2 is associated with severe COVID-19. Our results identify robust genetic signals relating to key host antiviral defence mechanisms and mediators of inflammatory organ damage in COVID-19. Both mechanisms may be amenable to targeted treatment with existing drugs. However, large-scale randomized clinical trials will be essential before any change to clinical practice

Global, regional, and national disability-adjusted life-years (DALYs) for 359 diseases and injuries and healthy life expectancy (HALE) for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017.

How long one lives, how many years of life are spent in good and poor health, and how the population's state of health and leading causes of disability change over time all have implications for policy, planning, and provision of services. We comparatively assessed the patterns and trends of healthy life expectancy (HALE), which quantifies the number of years of life expected to be lived in good health, and the complementary measure of disability-adjusted life-years (DALYs), a composite measure of disease burden capturing both premature mortality and prevalence and severity of ill health, for 359 diseases and injuries for 195 countries and territories over the past 28 years. Methods We used data for age-specific mortality rates, years of life lost (YLLs) due to premature mortality, and years lived with disability (YLDs) from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 to calculate HALE and DALYs from 1990 to 2017. We calculated HALE using age-specific mortality rates and YLDs per capita for each location, age, sex, and year. We calculated DALYs for 359 causes as the sum of YLLs and YLDs. We assessed how observed HALE and DALYs differed by country and sex from expected trends based on Socio-demographic Index (SDI). We also analysed HALE by decomposing years of life gained into years spent in good health and in poor health, between 1990 and 2017, and extra years lived by females compared with males. Findings Globally, from 1990 to 2017, life expectancy at birth increased by 7·4 years (95% uncertainty interval 7·1-7·8), from 65·6 years (65·3-65·8) in 1990 to 73·0 years (72·7-73·3) in 2017. The increase in years of life varied from 5·1 years (5·0-5·3) in high SDI countries to 12·0 years (11·3-12·8) in low SDI countries. Of the additional years of life expected at birth, 26·3% (20·1-33·1) were expected to be spent in poor health in high SDI countries compared with 11·7% (8·8-15·1) in low-middle SDI countries. HALE at birth increased by 6·3 years (5·9-6·7), from 57·0 years (54·6-59·1) in 1990 to 63·3 years (60·5-65·7) in 2017. The increase varied from 3·8 years (3·4-4·1) in high SDI countries to 10·5 years (9·8-11·2) in low SDI countries. Even larger variations in HALE than these were observed between countries, ranging from 1·0 year (0·4-1·7) in Saint Vincent and the Grenadines (62·4 years [59·9-64·7] in 1990 to 63·5 years [60·9-65·8] in 2017) to 23·7 years (21·9-25·6) in Eritrea (30·7 years [28·9-32·2] in 1990 to 54·4 years [51·5-57·1] in 2017). In most countries, the increase in HALE was smaller than the increase in overall life expectancy, indicating more years lived in poor health. In 180 of 195 countries and territories, females were expected to live longer than males in 2017, with extra years lived varying from 1·4 years (0·6-2·3) in Algeria to 11·9 years (10·9-12·9) in Ukraine. Of the extra years gained, the proportion spent in poor health varied largely across countries, with less than 20% of additional years spent in poor health in Bosnia and Herzegovina, Burundi, and Slovakia, whereas in Bahrain all the extra years were spent in poor health. In 2017, the highest estimate of HALE at birth was in Singapore for both females (75·8 years [72·4-78·7]) and males (72·6 years [69·8-75·0]) and the lowest estimates were in Central African Republic (47·0 years [43·7-50·2] for females and 42·8 years [40·1-45·6] for males). Globally, in 2017, the five leading causes of DALYs were neonatal disorders, ischaemic heart disease, stroke, lower respiratory infections, and chronic obstructive pulmonary disease. Between 1990 and 2017, age-standardised DALY rates decreased by 41·3% (38·8-43·5) for communicable diseases and by 49·8% (47·9-51·6) for neonatal disorders. For non-communicable diseases, global DALYs increased by 40·1% (36·8-43·0), although age-standardised DALY rates decreased by 18·1% (16·0-20·2)

Measuring progress from 1990 to 2017 and projecting attainment to 2030 of the health-related Sustainable Development Goals for 195 countries and territories: a systematic analysis for the Global Burden of Disease Study 2017

Background: Efforts to establish the 2015 baseline and monitor early implementation of the UN Sustainable Development Goals (SDGs) highlight both great potential for and threats to improving health by 2030. To fully deliver on the SDG aim of “leaving no one behind”, it is increasingly important to examine the health-related SDGs beyond national-level estimates. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2017 (GBD 2017), we measured progress on 41 of 52 health-related SDG indicators and estimated the health-related SDG index for 195 countries and territories for the period 1990–2017, projected indicators to 2030, and analysed global attainment. Methods: We measured progress on 41 health-related SDG indicators from 1990 to 2017, an increase of four indicators since GBD 2016 (new indicators were health worker density, sexual violence by non-intimate partners, population census status, and prevalence of physical and sexual violence [reported separately]). We also improved the measurement of several previously reported indicators. We constructed national-level estimates and, for a subset of health-related SDGs, examined indicator-level differences by sex and Socio-demographic Index (SDI) quintile. We also did subnational assessments of performance for selected countries. To construct the health-related SDG index, we transformed the value for each indicator on a scale of 0–100, with 0 as the 2\ub75th percentile and 100 as the 97\ub75th percentile of 1000 draws calculated from 1990 to 2030, and took the geometric mean of the scaled indicators by target. To generate projections through 2030, we used a forecasting framework that drew estimates from the broader GBD study and used weighted averages of indicator-specific and country-specific annualised rates of change from 1990 to 2017 to inform future estimates. We assessed attainment of indicators with defined targets in two ways: first, using mean values projected for 2030, and then using the probability of attainment in 2030 calculated from 1000 draws. We also did a global attainment analysis of the feasibility of attaining SDG targets on the basis of past trends. Using 2015 global averages of indicators with defined SDG targets, we calculated the global annualised rates of change required from 2015 to 2030 to meet these targets, and then identified in what percentiles the required global annualised rates of change fell in the distribution of country-level rates of change from 1990 to 2015. We took the mean of these global percentile values across indicators and applied the past rate of change at this mean global percentile to all health-related SDG indicators, irrespective of target definition, to estimate the equivalent 2030 global average value and percentage change from 2015 to 2030 for each indicator. Findings: The global median health-related SDG index in 2017 was 59\ub74 (IQR 35\ub74–67\ub73), ranging from a low of 11\ub76 (95% uncertainty interval 9\ub76–14\ub70) to a high of 84\ub79 (83\ub71–86\ub77). SDG index values in countries assessed at the subnational level varied substantially, particularly in China and India, although scores in Japan and the UK were more homogeneous. Indicators also varied by SDI quintile and sex, with males having worse outcomes than females for non-communicable disease (NCD) mortality, alcohol use, and smoking, among others. Most countries were projected to have a higher health-related SDG index in 2030 than in 2017, while country-level probabilities of attainment by 2030 varied widely by indicator. Under-5 mortality, neonatal mortality, maternal mortality ratio, and malaria indicators had the most countries with at least 95% probability of target attainment. Other indicators, including NCD mortality and suicide mortality, had no countries projected to meet corresponding SDG targets on the basis of projected mean values for 2030 but showed some probability of attainment by 2030. For some indicators, including child malnutrition, several infectious diseases, and most violence measures, the annualised rates of change required to meet SDG targets far exceeded the pace of progress achieved by any country in the recent past. We found that applying the mean global annualised rate of change to indicators without defined targets would equate to about 19% and 22% reductions in global smoking and alcohol consumption, respectively; a 47% decline in adolescent birth rates; and a more than 85% increase in health worker density per 1000 population by 2030. Interpretation: The GBD study offers a unique, robust platform for monitoring the health-related SDGs across demographic and geographic dimensions. Our findings underscore the importance of increased collection and analysis of disaggregated data and highlight where more deliberate design or targeting of interventions could accelerate progress in attaining the SDGs. Current projections show that many health-related SDG indicators, NCDs, NCD-related risks, and violence-related indicators will require a concerted shift away from what might have driven past gains—curative interventions in the case of NCDs—towards multisectoral, prevention-oriented policy action and investments to achieve SDG aims. Notably, several targets, if they are to be met by 2030, demand a pace of progress that no country has achieved in the recent past. The future is fundamentally uncertain, and no model can fully predict what breakthroughs or events might alter the course of the SDGs. What is clear is that our actions—or inaction—today will ultimately dictate how close the world, collectively, can get to leaving no one behind by 2030