Mechanosensory trichome cells evoke a mechanical stimuli-induced immune response in plants

Perception of pathogen-derived ligands by corresponding host receptors is a pivotal strategy in eukaryotic innate immunity. In plants, this is complemented by circadian anticipation of infection timing, promoting basal resistance even in the absence of pathogen threat. Here, we report that trichomes, hair-like structures on the epidermis, directly sense external mechanical forces caused by raindrops to anticipate waterborne infections in Arabidopsis thaliana. Exposure of leaf surfaces to mechanical stimuli initiates the concentric propagation of intercellular calcium waves away from trichomes to induce defence-related genes. Propagating calcium waves enable effective immunity against pathogenic microbes through the calmodulin-binding transcription activator 3 (CAMTA3) and mitogen-activated protein kinases. We propose a novel layer of plant immunity in which trichomes function as mechanosensory cells to detect potential risks.

Timing HIV infection with a simple and accurate population viral dynamics model

Clinical trials for HIV prevention can require knowledge of infection times to subsequently determine protective drug levels. Yet, infection timing is difficult when study visits are sparse. Using population nonlinear mixed-effects (pNLME) statistical inference and viral loads from 46 RV217 study participants, we developed a relatively simple HIV primary infection model that achieved an excellent fit to all data. We also discovered that Aptima assay values from the study strongly correlated with viral loads, enabling imputation of very early viral loads for 28/46 participants. Estimated times between infecting exposures and first positives were generally longer than prior estimates (average of two weeks) and were robust to missing viral upslope data. On simulated data, we found that tighter sampling before diagnosis improved estimation more than tighter sampling after diagnosis. Sampling weekly before and monthly after diagnosis was a pragmatic design for good timing accuracy. Our pNLME timing approach is widely applicable to other infections with existing mathematical models. The present model could be used to simulate future HIV trials and may help estimate protective thresholds from the recently completed antibody-mediated prevention trials.

Features of the epizootiological process for the main helminthiasis in cattle in the Amur region

The effectiveness of the fight against helminthiases depends on the knowledge of their epizootology, age and seasonal dynamics. The Amur Region is located in a sharp continental climate zone, which affects the living conditions and health status of farm animals, including the development of various parasitic diseases that negatively affect the productivity of farm animals. The biological cycles of helminths are characterized by seasonal dynamics of development, since most of them take place with the participation of intermediate hosts that are sensitive to changes in climatic conditions (temperature, amount of precipitation), as well as to other factors. The determination of the onset of infection timing, the most unfavorable seasons and the main types of helminths are necessary for the prevention of helminthiasis in each specific region. It has been established that the basis of the population structure of helminthiases in cattle under the conditions of the Amur Region is trongylatoses, strongyloidiasis, neoascariasis and moniesiasis. The first eggs and larvae of Strongylata spp. Found in February – April. The greatest extent of invasion was observed in the winter period (February). Moniezia benedeni, as well as Neoascaris vitulorum, had the highest infection rates in the autumnwinter period. At the same time, in the annual dynamics, the first eggs of helminths in both species were found in February. Cases of detection of other helminths in cattle were first recorded mainly in the spring. Thus, the infection of cattle with helminths in the Amur Region does not depend on the grazing season, which should be taken into account when developing plans for anthelmintic measures in livestock farms.

SARS-CoV-2 antibody magnitude and detectability are driven by disease severity, timing, and assay

ABSTRACTSerosurveillance studies are critical for estimating SARS-CoV-2 transmission and immunity, but interpretation of results is currently limited by poorly defined variability in the performance of antibody assays to detect seroreactivity over time in individuals with different clinical presentations. We measured longitudinal antibody responses to SARS-CoV-2 in plasma samples from a diverse cohort of 128 individuals over 160 days using 14 binding and neutralization assays. For all assays, we found a consistent and strong effect of disease severity on antibody magnitude, with fever, cough, hospitalization, and oxygen requirement explaining much of this variation. We found that binding assays measuring responses to spike protein had consistently higher correlation with neutralization than those measuring responses to nucleocapsid, regardless of assay format and sample timing. However, assays varied substantially with respect to sensitivity during early convalescence and in time to seroreversion. Variations in sensitivity and durability were particularly dramatic for individuals with mild infection, who had consistently lower antibody titers and represent the majority of the infected population, with sensitivities often differing substantially from reported test characteristics (e.g., amongst commercial assays, sensitivity at 6 months ranged from 33% for ARCHITECT IgG to 98% for VITROS Total Ig). Thus, the ability to detect previous infection by SARS-CoV-2 is highly dependent on the severity of the initial infection, timing relative to infection, and the assay used. These findings have important implications for the design and interpretation of SARS-CoV-2 serosurveillance studies.

Factors influencing estimates of HIV-1 infection timing using BEAST

While large datasets of HIV-1 sequences are increasingly being generated, many studies rely on a single gene or fragment of the genome and few comparative studies across genes have been done. We performed genome-based and gene-specific Bayesian phylogenetic analyses to investigate how certain factors impact estimates of the infection dates in an acute HIV-1 infection cohort, RV217. In this cohort, HIV-1 diagnosis corresponded to the first RNA positive test and occurred a median of four days after the last negative test, allowing us to compare timing estimates using BEAST to a narrow window of infection. We analyzed HIV-1 sequences sampled one week, one month and six months after HIV-1 diagnosis in 39 individuals. We found that shared diversity and temporal signal was limited in acute infection, and insufficient to allow timing inferences in the shortest HIV-1 genes, thus dated phylogenies were primarily analyzed for env, gag, pol and near full-length genomes. There was no one best-fitting model across participants and genes, though relaxed molecular clocks (73% of best-fitting models) and the Bayesian skyline (49%) tended to be favored. For infections with single founders, the infection date was estimated to be around one week pre-diagnosis for env (IQR: 3–9 days) and gag (IQR: 5–9 days), whilst the genome placed it at a median of 10 days (IQR: 4–19). Multiply-founded infections proved problematic to date. Our ability to compare timing inferences to precise estimates of HIV-1 infection (within a week) highlights that molecular dating methods can be applied to within-host datasets from early infection. Nonetheless, our results also suggest caution when using uniform clock and population models or short genes with limited information content.

Fusarium Head Blight: Effect of Infection Timing on Spread of Fusarium graminearum and Spatial Distribution of Deoxynivalenol within Wheat Spikes

Most studies of Fusarium head blight (FHB) focused on wheat infection at anthesis. Less is known about infections at later stages. In this study, the effect of infection timing on the development of FHB and the distribution of fungal biomass and deoxynivalenol (DON) along wheat spikes was investigated. Under greenhouse conditions, two wheat varieties were point-inoculated with Fusarium graminearum starting from anthesis until 25 days after anthesis. The fungus and fungal DNA were isolated from the centers and the bases of all the spikes but not from the tips for all inoculation times and both varieties. In each variety, the amount of fungal DNA and the content of DON and deoxynivalenol-3-glucoside (DON-3-G) were higher in the center than in the base for all inoculation times. A positive correlation was found between the content of fungal DNA and DON in the centers as well as the bases of both varieties. This study showed that F. graminearum grows downward within infected wheat spikes and that the accumulation of DON is largely confined to the colonized tissue. Moreover, F. graminearum was able to infect wheat kernels and cause contamination with mycotoxins even when inoculated 25 days after anthesis.

Malaria during pregnancy and transplacental transfer of Kaposi sarcoma-associated herpesvirus (KSHV) antibodies: a cohort study of Kenyan mother and child pairs

Background Kaposi sarcoma-associated herpesvirus (KSHV) seroprevalence in sub-Saharan African children can range up to 50% by age 2 years but factors affecting early age of KSHV infection are not well understood. Malaria during pregnancy has been associated with hindered transplacental transfer of antibodies to several pathogens but whether it affects transplacental transfer of KSHV antibodies is unknown. We aimed to determine if in utero malaria exposure reduced the transfer of KSHV antibodies across the placenta. Methods A cohort study in Kisumu, Kenya enrolled pregnant women at their first antenatal clinic (ANC) visit and followed them through delivery. We included 70 KSHV-positive, HIV-negative mothers and their children. KSHV antibody levels were measured by ELISA (K8.1, ORF73) and multiplex assay (K8.1, ORF73, K10.5, ORF38, ORF50). Transplacental transfer of antibodies was measured by the cord to maternal blood ratio (CMR) of KSHV antibodies. Malaria during pregnancy was defined as detection of Plasmodium falciparum (Pf) DNA at any ANC visit or delivery. Among women with malaria during pregnancy, we examined time of last malaria infection prior to delivery (< 27 vs. 27+ weeks gestation) and malaria incidence rate (MIR) (episodes/100 person-weeks). Results KSHV seroprevalence (positive for K8.1 or ORF73 by ELISA) among pregnant women was 88%. Neither malaria during pregnancy, malaria infection timing, nor MIR were associated with maternal delivery KSHV antibody blood levels. Maternal delivery and cord blood KSHV antibody levels were highly correlated but these correlations did not differ by malaria during pregnancy. KSHV transplacental antibody transfer was not associated with malaria during pregnancy, malaria infection timing, nor MIR. Conclusions Malaria during pregnancy does not appear to affect transfer of KSHV antibodies across the placenta.

Dielectric Spectroscopy to Improve the Production of rAAV Used in Gene Therapy

The insect cell-baculovirus expression vector system is an established method for large scale recombinant adeno-associated virus (rAAV) production, largely due to its scalability and high volumetric productivities. During rAAV production it is critical to monitor process parameters such as Spodoptera frugiperda (Sf9) cell concentration, infection timing, and cell harvest viabilities since they can have a significant influence on rAAV productivity and product quality. Herein we developed the use of dielectric spectroscopy as a process analytical technology (PAT) tool used to continuously monitor the production of rAAV in 2 L stirred tank bioreactors, achieving enhanced control over the production process. This study resulted in improved manufacturing robustness through continuous monitoring of cell culture parameters, eliminating sampling needs, increasing the accuracy of infection timing, and reliably estimating the time of harvest. To increase the accuracy of baculovirus infection timing, the cell growth/permittivity model was coupled to a feedback loop with real-time monitoring. This system was able to predict baculovirus infection timing up to 24 h in advance for greatly improved accuracy of infection and ensuring consistent high rAAV productivities. Furthermore, predictive models were developed based on the dielectric measurements of the culture. These multiple linear regression-based models resulted in correlation coefficients (Q2) of 0.89 for viable cell concentration, 0.97 for viability, and 0.92 for cell diameter. Finally, models were developed to predict rAAV titer providing the capability to distinguish in real time between high and low titer production batches.