Tracking mite trophic interactions by multiplex PCR

BACKGROUND A thorough knowledge of trophic webs in agroecosystems is essential to achieve successful biological pest control. Phytoseiid mites are the most efficient natural enemies of tetranychid mites, which include several important pests worldwide. Nevertheless, phytoseiids may feed on other food sources including other microarthropods, plants and even other phytoseiids (intraguild predation), which can interfere with biological control services. Molecular gut content analysis is a valuable tool for characterizing trophic interactions, mainly when working on microarthropods such as mites. We have designed new primers for Phytoseiidae, Tetranychidae and Thysanoptera identification and they have been multiplexed in a polymerase chain reaction (PCR) together with universal plant primers. Additionally, we have estimated prey DNA detectability success over time (DS50) considering the most probable events in Spanish citrus orchards: the phytoseiid Euseius stipulatus as a predator, the phytoseiid Phytoseiulus persimilis as intraguild prey, and the thrips Frankliniella occidentalis and Anaphothrips obscurus as alternative prey to Tetranychus urticae. RESULTS The designed multiplex PCR allows the identification of phytoseiids (both predator and intraguild prey) and detects alternative food sources mentioned above in the gut of the phytoseiid predator. DS50 for E. stipulatus as the predator were 1.3, 2.3 and 18.7 h post feeding for F. occidentalis, A. obscurus and P. persimilis as prey, respectively. CONCLUSION Tracking of the trophic relationships within the citrus acarofauna, and the unveiling of the role of alternative food sources will pave the way for enhancing T. urticae biological control. This multiplex PCR approach could be applicable for these purposes in similar agroecosystems

The Genetic Structure of Leishmania infantum Populations in Brazil and Its Possible Association with the Transmission Cycle of Visceral Leishmaniasis

Leishmania infantum is the etiologic agent of visceral leishmaniasis (VL) in the Americas, Mediterranean basin and West and Central Asia. Although the geographic structure of L. infantum populations from the Old World have been described, few studies have addressed the population structure of this parasite in the Neotropical region. We employed 14 microsatellites to analyze the population structure of the L. infantum strains isolated from humans and dogs from most of the Brazilian states endemic for VL and from Paraguay. The results indicate a low genetic diversity, high inbreeding estimates and a depletion of heterozygotes, which together indicate a predominantly clonal breeding system, but signs of sexual events are also present. Three populations were identified from the clustering analysis, and they were well supported by F statistics inferences and partially corroborated by distance-based. POP1 (111 strains) was observed in all but one endemic area. POP2 (31 strains) is also well-dispersed, but it was the predominant population in Mato Grosso (MT). POP3 (31 strains) was less dispersed, and it was observed primarily in Mato Grosso do Sul (MS). Strains originated from an outbreak of canine VL in Southern Brazil were grouped in POP1 with those from Paraguay, which corroborates the hypothesis of dispersal from Northeastern Argentina and Paraguay. The distribution of VL in MS seems to follow the west-east construction of the Bolivia-Brazil pipeline from Corumbá municipality. This may have resulted in a strong association of POP3 and Lutzomyia cruzi, which is the main VL vector in Corumbá, and a dispersion of this population in this region that was shaped by human interference. This vector also occurs in MT and may influence the structure of POP2. This paper presents significant advances in the understanding of the population structure of L. infantum in Brazil and its association with eco-epidemiological aspects of VL

Comparative Microsatellite Typing of New World Leishmania infantum Reveals Low Heterogeneity among Populations and Its Recent Old World Origin

Leishmania infantum (syn. L. chagasi) is the causative agent of visceral leishmaniasis (VL) in the New World (NW) with endemic regions extending from southern USA to northern Argentina. The two hypotheses about the origin of VL in the NW suggest (1) recent importation of L. infantum from the Old World (OW), or (2) an indigenous origin and a distinct taxonomic rank for the NW parasite. Multilocus microsatellite typing was applied in a survey of 98 L. infantum isolates from different NW foci. The microsatellite profiles obtained were compared to those of 308 L. infantum and 20 L. donovani strains from OW countries previously assigned to well-defined populations. Two main populations were identified for both NW and OW L. infantum. Most of the NW strains belonged to population 1, which corresponded to the OW MON-1 population. However, the NW population was much more homogeneous. A second, more heterogeneous, population comprised most Caribbean strains and corresponded to the OW non-MON-1 population. All Brazilian L. infantum strains belonged to population 1, although they represented 61% of the sample and originated from 9 states. Population analysis including the OW L. infantum populations indicated that the NW strains were more similar to MON-1 and non-MON-1 sub-populations of L. infantum from southwest Europe, than to any other OW sub-population. Moreover, similarity between NW and Southwest European L. infantum was higher than between OW L. infantum from distinct parts of the Mediterranean region, Middle East and Central Asia. No correlation was found between NW L. infantum genotypes and clinical picture or host background. This study represents the first continent-wide analysis of NW L. infantum population structure. It confirmed that the agent of VL in the NW is L. infantum and that the parasite has been recently imported multiple times to the NW from southwest Europe

Global age-sex-specific fertility, mortality, healthy life expectancy (HALE), and population estimates in 204 countries and territories, 1950-2019: a comprehensive demographic analysis for the Global Burden of Disease Study 2019.

BACKGROUND: Accurate and up-to-date assessment of demographic metrics is crucial for understanding a wide range of social, economic, and public health issues that affect populations worldwide. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 produced updated and comprehensive demographic assessments of the key indicators of fertility, mortality, migration, and population for 204 countries and territories and selected subnational locations from 1950 to 2019. METHODS: 8078 country-years of vital registration and sample registration data, 938 surveys, 349 censuses, and 238 other sources were identified and used to estimate age-specific fertility. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate age-specific fertility rates for 5-year age groups between ages 15 and 49 years. With extensions to age groups 10-14 and 50-54 years, the total fertility rate (TFR) was then aggregated using the estimated age-specific fertility between ages 10 and 54 years. 7417 sources were used for under-5 mortality estimation and 7355 for adult mortality. ST-GPR was used to synthesise data sources after correction for known biases. Adult mortality was measured as the probability of death between ages 15 and 60 years based on vital registration, sample registration, and sibling histories, and was also estimated using ST-GPR. HIV-free life tables were then estimated using estimates of under-5 and adult mortality rates using a relational model life table system created for GBD, which closely tracks observed age-specific mortality rates from complete vital registration when available. Independent estimates of HIV-specific mortality generated by an epidemiological analysis of HIV prevalence surveys and antenatal clinic serosurveillance and other sources were incorporated into the estimates in countries with large epidemics. Annual and single-year age estimates of net migration and population for each country and territory were generated using a Bayesian hierarchical cohort component model that analysed estimated age-specific fertility and mortality rates along with 1250 censuses and 747 population registry years. We classified location-years into seven categories on the basis of the natural rate of increase in population (calculated by subtracting the crude death rate from the crude birth rate) and the net migration rate. We computed healthy life expectancy (HALE) using years lived with disability (YLDs) per capita, life tables, and standard demographic methods. Uncertainty was propagated throughout the demographic estimation process, including fertility, mortality, and population, with 1000 draw-level estimates produced for each metric. FINDINGS: The global TFR decreased from 2·72 (95% uncertainty interval [UI] 2·66-2·79) in 2000 to 2·31 (2·17-2·46) in 2019. Global annual livebirths increased from 134·5 million (131·5-137·8) in 2000 to a peak of 139·6 million (133·0-146·9) in 2016. Global livebirths then declined to 135·3 million (127·2-144·1) in 2019. Of the 204 countries and territories included in this study, in 2019, 102 had a TFR lower than 2·1, which is considered a good approximation of replacement-level fertility. All countries in sub-Saharan Africa had TFRs above replacement level in 2019 and accounted for 27·1% (95% UI 26·4-27·8) of global livebirths. Global life expectancy at birth increased from 67·2 years (95% UI 66·8-67·6) in 2000 to 73·5 years (72·8-74·3) in 2019. The total number of deaths increased from 50·7 million (49·5-51·9) in 2000 to 56·5 million (53·7-59·2) in 2019. Under-5 deaths declined from 9·6 million (9·1-10·3) in 2000 to 5·0 million (4·3-6·0) in 2019. Global population increased by 25·7%, from 6·2 billion (6·0-6·3) in 2000 to 7·7 billion (7·5-8·0) in 2019. In 2019, 34 countries had negative natural rates of increase; in 17 of these, the population declined because immigration was not sufficient to counteract the negative rate of decline. Globally, HALE increased from 58·6 years (56·1-60·8) in 2000 to 63·5 years (60·8-66·1) in 2019. HALE increased in 202 of 204 countries and territories between 2000 and 2019. INTERPRETATION: Over the past 20 years, fertility rates have been dropping steadily and life expectancy has been increasing, with few exceptions. Much of this change follows historical patterns linking social and economic determinants, such as those captured by the GBD Socio-demographic Index, with demographic outcomes. More recently, several countries have experienced a combination of low fertility and stagnating improvement in mortality rates, pushing more populations into the late stages of the demographic transition. Tracking demographic change and the emergence of new patterns will be essential for global health monitoring. FUNDING: Bill & Melinda Gates Foundation