The haplolethal gene wupA of Drosophila exhibits potential as a target for an X-poisoning gene drive.

A synthetic gene drive that targets haplolethal genes on the X chromosome can skew the sex ratio toward males. Like an "X-shredder," it does not involve "homing," and that has advantages including the reduction of gene drive resistance allele formation. We examine this "X-poisoning" strategy by targeting 4 of the 11 known X-linked haplolethal/haplosterile genes of Drosophila melanogaster with CRISPR/Cas9. We find that targeting the wupA gene during spermatogenesis skews the sex ratio so fewer than 14% of progeny are daughters. That is unless we cross the mutagenic males to X^XY female flies that bear attached-X chromosomes, which reverses the inheritance of the poisoned X chromosome so that sons inherit it from their father, in which case only 2% of the progeny are sons. These sex ratio biases suggest that most of the CRISPR/Cas9 mutants we induced in the wupA gene are haplolethal but some are recessive lethal. The males generating wupA mutants do not suffer from reduced fertility; rather, the haplolethal mutants arrest development in the late stages of embryogenesis well after fertilized eggs have been laid. This provides a distinct advantage over genetic manipulation strategies involving sterility which can be countered by the remating of females. We also find that wupA mutants that destroy the nuclear localization signal of shorter isoforms are not haplolethal as long as the open reading frame remains intact. Like D. melanogaster, wupA orthologs of Drosophila suzukii and Anopheles mosquitos are found on X chromosomes making wupA a viable X-poisoning target in multiple species.

A systematic review of dermatologic manifestations among adult patients with COVID-19 diagnosis.

BACKGROUND: Infection with COVID-19 is characterized by respiratory, gastrointestinal and neurologic symptoms. However, limited evidence exists of the involvement of the integumentary system among COVID-19 patients and evidence suggests that these symptoms may even be the first presenting sign. OBJECTIVE: To systematically evaluate the literature published on dermatologic signs of COVID-19 in order to educate doctors about the dermatologic signs of COVID-19 infection. METHODS: Lit COVID, World Health Organization COVID-19 database and PubMed were searched using terminology to identify adult patients with confirmed COVID-19 infection and dermatologic manifestations of disease. The last search was completed on 13 July 2020. RESULTS: There were 802 reports found. After exclusion, 20 articles were found with 347 patients with confirmed COVID-19 infection. Within these articles, 27 different skin signs were reported. LIMITATIONS: Limitations of this review include the recency of COVID-19 infection; so, there are limited published reports and that many reports are not by dermatologists, and so, the cutaneous signs may be misdiagnosed or misdescribed. CONCLUSION: Dermatologic manifestations of COVID-19 may be the first presenting sign of infection; so, dermatologists and doctors examining the skin should be aware of the virus's influence on the integumentary system in order to promptly diagnose and treat the infected patients.

Necroptosis suppresses inflammation via termination of TNF- or LPS-induced cytokine and chemokine production.

TNF promotes a regulated form of necrosis, called necroptosis, upon inhibition of caspase activity in cells expressing RIPK3. Because necrosis is generally more pro-inflammatory than apoptosis, it is widely presumed that TNF-induced necroptosis may be detrimental in vivo due to excessive inflammation. However, because TNF is intrinsically highly pro-inflammatory, due to its ability to trigger the production of multiple cytokines and chemokines, rapid cell death via necroptosis may blunt rather than enhance TNF-induced inflammation. Here we show that TNF-induced necroptosis potently suppressed the production of multiple TNF-induced pro-inflammatory factors due to RIPK3-dependent cell death. Similarly, necroptosis also suppressed LPS-induced pro-inflammatory cytokine production. Consistent with these observations, supernatants from TNF-stimulated cells were more pro-inflammatory than those from TNF-induced necroptotic cells in vivo. Thus necroptosis attenuates TNF- and LPS-driven inflammation, which may benefit intracellular pathogens that evoke this mode of cell death by suppressing host immune responses.

ECG of the month. Electrocardiogram in a man with chronic kidney failure. ECG is abnormal and indicative of heart disease.

A 70-year-old man came to the Access to Primary Care Clinic at the Interim LSU Public Hospital because he had been told at another hospital that he needed a kidney doctor. The patient had a history of high blood pressure, type 2 diabetes mellitus, long-standing kidney disease, an above the knee amputation on the left, gout, a possible coronary stent procedure five years ago, and recently poor appetite and inability to care for himself. He had a long history of medical noncompliance and was taking no medications when he came to the hospital. He denied all cardiac symptoms, including chest discomfort. He was admitted to hospital because of a blood pressure of 240/110 mmHg, a serum creatinine of 6.0 mg/dL, and an estimated glomerular filtration rate of 11 mL/min - i.e., chronic kidney disease, stage V. His electrocardiogram was read by the computer as normal (Figure 1).

Mitochondrial DNA variants in Drosophila melanogaster are expressed at the level of the organismal phenotype.

A plethora of experimental studies use mtDNA as a marker of demographic processes without questioning the possibility that selection may bias their interpretations. We studied four lines of Drosophila melanogaster that have a standardized nuclear DNA but variable mtDNA. We completed the sequencing of the mitochondrial genomes (excluding the A+T rich region) and compiled the differences. We then assayed male influence on oviposition, starvation resistance, lipid proportion and physical activity. We discuss these results in terms of the known differences between the lines and conclude that naturally occurring mtDNA variants in D. melanogaster are expressed at the level of the organismal phenotype.

A network model of E. coli O157 transmission within a typical UK dairy herd: the effect of heterogeneity and clustering on the prevalence of infection.

Cattle are considered to be the main reservoir for Vero cytotoxin-producing Escherichia coli (VTEC) O157, a cause of food-poisoning (and even death) in humans. Here, the transmission of E. coli O157 within a typical UK dairy herd is modelled using a semi-stochastic network model. The model incorporates demographic as well as infection processes. Indirect transmission is modelled homogeneously, while direct transmission is modelled via a dynamic contact network. The aim was to investigate the effects of heterogeneity and clustering on the prevalence of infection within the herd and discover whether, particularly in terms of choosing an intervention strategy, it is necessary to include heterogeneity in direct contacts when modelling this sort of system. Results show that heterogeneity in direct contacts can make it more difficult for the pathogen to persist, particularly when the average number of contacts (per animal) in each group is small. They also show that the relationship between clustering and prevalence is not simple. For example, increasing the average number of contacts can increase clustering and prevalence. However, when the average number of contacts in each group is sufficiently high, higher clustering leads to lower prevalence. It would seem that clustering can aid the flow of infection under certain circumstances, but hinder it under others (probably by preventing wider dissemination). Further results show that indirect transmission (as it is modelled here) effectively removes the effect of heterogeneity in direct contacts. In terms of investigating proposed interventions, the results suggest that a network model would only be required if there was evidence to suggest that direct transmission was the major source of infection.

A semi-stochastic model for Salmonella infection in a multi-group herd.

A multi-group semi-stochastic model is formulated to identify possible causes of why different strains of Salmonella develop so much variation in their infection dynamics in UK dairy herds. The model includes demography (managed populations) and various types of transmission: direct, pseudovertical and indirect (via free-living infectious units in the environment). The effects of herd size and epidemiological parameters on mean prevalence of infection and mean time until fade out are investigated. Numerical simulation shows that higher pathogen-induced mortality, shorter infectious period, more persistent immune response and more rapid removal of faeces result in a lower mean prevalence of infection, a shorter mean time until fade out, and a greater probability of fade out of infection within 600 days. Combining these results and those for the deterministic counterpart could explain differences in observed epidemiological patterns and help to identify the factors inducing the decline in reported cases of epidemic strains such as DT104 in cattle. We further investigate the effect of group structure on the probability of a major outbreak by using the stochastic threshold theory in homogeneous populations and that in heterogeneous populations. Numerical studies suggest that group structure makes major outbreaks less likely than would be the case in a homogeneous population with the same basic reproduction number. Moreover, some control strategies are suggested by investigating the effect of epidemiological parameters on the probability of an epidemic.

Infection in social networks: using network analysis to identify high-risk individuals.

Simulation studies using susceptible-infectious-recovered models were conducted to estimate individuals' risk of infection and time to infection in small-world and randomly mixing networks. Infection transmitted more rapidly but ultimately resulted in fewer infected individuals in the small-world, compared with the random, network. The ability of measures of network centrality to identify high-risk individuals was also assessed. "Centrality" describes an individual's position in a population; numerous parameters are available to assess this attribute. Here, the authors use the centrality measures degree (number of contacts), random-walk betweenness (a measure of the proportion of times an individual lies on the path between other individuals), shortest-path betweenness (the proportion of times an individual lies on the shortest path between other individuals), and farness (the sum of the number of steps between an individual and all other individuals). Each was associated with time to infection and risk of infection in the simulated outbreaks. In the networks examined, degree (which is the most readily measured) was at least as good as other network parameters in predicting risk of infection. Identification of more central individuals in populations may be used to inform surveillance and infection control strategies.

Quantifying uncertainty associated with microbial count data: a Bayesian approach.

We consider the problem of estimating bacterial concentration in a substance, given microbial count data. A Bayesian approach is proposed which naturally allows the incorporation of both plate-count data and extra information from confirmatory tests such as genotyping by polymerase chain reaction (PCR). The estimation methods yield posterior credible regions for bacterial concentration, in contrast to the previous methods, which generally only produce point estimates. The approach is illustrated with specific reference to the enumeration of the food-borne pathogen Escherichia coli O157 by spiral plating, although the methodology can be applied to any bacterium or counting method of interest. The results obtained provide guidance to the experimenter as to the number of confirmatory tests which should be performed, and also suggest that in the initial plate count one should err on the side of including rather than excluding colonies whose genotype seems unclear.

Two sets of HLA Class II DRB and DQB1 alleles co-segregate among family members in a single maternal haplotype.

HLA class II typing by sequence specific oligonucleotide probes (SSOP) on the family of a Burkit's Lymphoma patient produced hybridization patterns indicating the presence of two DRB1, and two linked DQB1 genes on the same maternal chromosome. DRB and DQB1 exon 2 amplification products associated with the novel maternal haplotype were identified by DNA typing techniques: These products corresponded to DRB1*0101, DRB1*1501, DRB5*01, DQB1*0501 and DQB1*0602 alleles. These alleles were seen to co-segregate among siblings sharing the same maternal haplotype. The patient, his mother and two of his siblings each appeared to possess elements of three DRB1, DQA1 and DQB1 genes. HLA DNA typing results indicated that a DNA sequence of approximately 100 Kb, spanning the region between, and including, DRB1 and DQB1 genes was inserted into the maternal haplotype. Serological typing on EBV transformed B lymphocytes obtained from the patient's mother showed three expressed DRB1 antigens. Serology on EBV transformed patient's cells also indicated multiple DRB1 antigen expression. The expression of three DRB1 and DQB1 genes on the cells of this patient would make it virtually impossible to obtain a suitably matched unrelated stem cell donor.

Bayesian methods for estimating pathogen prevalence within groups of animals from faecal-pat sampling.

Pathogens such as Escherichia coli O157:H7 and Campylobacter spp. have been implicated in outbreaks of food poisoning in the UK and elsewhere. Domestic animals and wildlife are important reservoirs for both of these agents, and cross-contamination from faeces is believed to be responsible for many human outbreaks. Appropriate parameterisation of quantitative microbial-risk models requires representative data at all levels of the food chain. Our focus in this paper is on the early stages of the food chain-specifically, sampling issues which arise at the farm level. We estimated animal-pathogen prevalence from faecal-pat samples using a Bayesian method which reflected the uncertainties inherent in the animal-level prevalence estimates. (Note that prevalence here refers to the percentage of animals shedding the bacteria of interest). The method offers more flexibility than traditional, classical approaches: it allows the incorporation of prior belief, and permits the computation of a variety of distributional and numerical summaries, analogues of which often are not available through a classical framework. The Bayesian technique is illustrated with a number of examples reflecting the effects of a diversity of assumptions about the underlying processes. The technique appears to be both robust and flexible, and is useful when defecation rates in infected and uninfected groups are unequal, where population size is uncertain, and also where the microbiological-test sensitivity is imperfect. We also investigated the determination of the sample size necessary for determining animal-level prevalence from pat samples to within a pre-specified degree of accuracy.

Dose-response relationships for foot and mouth disease in cattle and sheep.

The relationships between the inhaled dose of foot and mouth disease virus and the outcomes of infection and disease were examined by fitting dose-response models to experimental data. The parameters for both the exponential and beta-poisson models were estimated using maximum likelihood and Bayesian methods. The median probability of infection given a single inhaled TCID50 was estimated to be 0.031 with 95% Bayesian credibility intervals (CI) of 0.018-0.052 for cattle, and 0.045 (CI = 0.024-0.080) for sheep. These estimates were used to construct dose-response curves and uncertainty distributions for use in quantitative risk assessments.

A stochastic model for disease transmission in a managed herd, motivated by Neospora caninum amongst dairy cattle.

A stochastic model for the spread of Neospora caninum infection within a herd of dairy cattle is studied, in particular the long-term (equilibrium) behaviour of the model. The model incorporates the interesting feature that total herd size is constrained to lie within a fairly small interval, but not held exactly constant. Approximations for the joint distribution of numbers of susceptible and infected individuals present in equilibrium are derived based upon a diffusion approximation to the infection process. The effect of both 'typical herd size' and 'the amount of permitted variation in herd size' upon disease prevalence in equilibrium are considered using both the exact equilibrium distribution of the process and our approximations.

Extension of life-span by loss of CHICO, a Drosophila insulin receptor substrate protein.

The Drosophila melanogaster gene chico encodes an insulin receptor substrate that functions in an insulin/insulin-like growth factor (IGF) signaling pathway. In the nematode Caenorhabditis elegans, insulin/IGF signaling regulates adult longevity. We found that mutation of chico extends fruit fly median life-span by up to 48% in homozygotes and 36% in heterozygotes. Extension of life-span was not a result of impaired oogenesis in chico females, nor was it consistently correlated with increased stress resistance. The dwarf phenotype of chico homozygotes was also unnecessary for extension of life-span. The role of insulin/IGF signaling in regulating animal aging is therefore evolutionarily conserved.