Phylodynamic modelling of foot-and-mouth disease virus sequence data

The under-reporting of cases of infectious diseases is a substantial impediment to the control and management of infectious diseases in both epidemic and endemic contexts. Information about infectious disease dynamics can be recovered from sequence data using time-varying coalescent approaches, and phylodynamic models have been developed in order to reconstruct demographic changes of the numbers of infected hosts through time. In this study I have demonstrated the general concordance between empirically observed epidemiological incidence data and viral demography inferred through analysis of foot-and-mouth disease virus VP1 coding sequences belonging to the CATHAY topotype over large temporal and spatial scales. However a more precise and robust relationship between the effective population size (

The epidemiology of foot-and-mouth disease at the wildlife-livestock interface in northern Tanzania

Foot-and-mouth disease (FMD), a disease of cloven hooved animals caused by FMD virus (FMDV), is one of the most economically devastating diseases of livestock worldwide. The global burden of disease is borne largely by livestock-keepers in areas of Africa and Asia where the disease is endemic and where many people rely on livestock for their livelihoods and food-security. Yet, there are many gaps in our knowledge of the drivers of FMDV circulation in these settings. In East Africa, FMD epidemiology is complicated by the circulation of multiple FMDV serotypes (distinct antigenic variants) and by the presence of large populations of susceptible wildlife and domestic livestock. The African buffalo (Syncerus caffer) is the only wildlife species with consistent evidence of high levels of FMDV infection, and East Africa contains the largest population of this species globally. To inform FMD control in this region, key questions relate to heterogeneities in FMD prevalence and impacts in different livestock management systems and to the role of wildlife as a potential source of FMDV for livestock. To develop FMD control strategies and make best use of vaccine control options, serotype-specific patterns of circulation need to be characterised. In this study, the impacts and epidemiology of FMD were investigated across a range of traditional livestock-keeping systems in northern Tanzania, including pastoralist, agro-pastoralist and rural smallholder systems. Data were generated through field studies and laboratory analyses between 2010 and 2015. The study involved analysis of existing household survey data and generated serological data from cross-sectional livestock and buffalo samples and longitudinal cattle samples. Serological analyses included non-structural protein ELISAs, serotype-specific solid-phase competitive ELISAs, with optimisation to detect East African FMDV variants, and virus neutralisation testing. Risk factors for FMDV infection and outbreaks were investigated through analysis of cross-sectional serological data in conjunction with a case-control outbreak analysis. A novel Bayesian modeling approach was developed to infer serotype-specific infection history from serological data, and combined with virus isolation data from FMD outbreaks to characterise temporal and spatial patterns of serotype-specific infection. A high seroprevalence of FMD was detected in both northern Tanzanian livestock (69%, [66.5 - 71.4%] in cattle and 48.5%, [45.7-51.3%] in small ruminants) and in buffalo (80.9%, [74.7-86.1%]). Four different serotypes of FMDV (A, O, SAT1 and SAT2) were isolated from livestock. Up to three outbreaks per year were reported by households and active surveillance highlighted up to four serial outbreaks in the same herds within three years. Agro-pastoral and pastoral livestock keepers reported more frequent FMD outbreaks compared to smallholders. Households in all three management systems reported that FMD outbreaks caused significant impacts on milk production and sales, and on animals’ draught power, hence on crop production, with implications for food security and livelihoods. Risk factor analyses showed that older livestock were more likely to be seropositive for FMD (Odds Ratio [OR] 1.4 [1.4-1.5] per extra year) and that cattle (OR 3.3 [2.7-4.0]) were more likely than sheep and goats to be seropositive. Livestock managed by agro-pastoralists (OR 8.1 [2.8-23.6]) or pastoralists (OR 7.1 [2.9-17.6]) were more likely to be seropositive compared to those managed by smallholders. Larger herds (OR: 1.02 [1.01-1.03] per extra bovine) and those that recently acquired new livestock (OR: 5.57 [1.01 – 30.91]) had increased odds of suffering an FMD outbreak. Measures of potential contact with buffalo or with other FMD susceptible wildlife did not increase the likelihood of FMD in livestock in either the cross-sectional serological analysis or case-control outbreak analysis. The Bayesian model was validated to correctly infer from ELISA data the most recent serotype to infect cattle. Consistent with the lack of risk factors related to wildlife contact, temporal and spatial patterns of exposure to specific FMDV serotypes were not tightly linked in cattle and buffalo. In cattle, four serial waves of different FMDV serotypes that swept through southern Kenyan and northern Tanzanian livestock populations over a four-year period dominated infection patterns. In contrast, only two serotypes (SAT1 and SAT2) dominated in buffalo populations. Key conclusions are that FMD has a substantial impact in traditional livestock systems in East Africa. Wildlife does not currently appear to act as an important source of FMDV for East African livestock, and control efforts in the region should initially focus on livestock management and vaccination strategies. A novel modeling approach greatly facilitated the interpretation of serological data and may be a potent epidemiological tool in the African setting. There was a clear temporal pattern of FMDV antigenic dominance across northern Tanzania and southern Kenya. Longer-term research to investigate whether serotype-specific FMDV sweeps are truly predictable, and to shed light on FMD post-infection immunity in animals exposed to serial FMD infections is warranted.

Acute phase proteins and biomarkers for health in chickens

Acute phase proteins (APPs) are proteins synthesised predominantly in the liver, whose plasma concentrations increase (positive APP) or decrease (negative APP) as a result of infection, inflammation, trauma and tissue injury. They also change as a result of the introduction of immunogens such as bacterial lipopolysaccharide (LPS), turpentine and vaccination. While publications on APPs in chickens are numerous, the limited availability of anti-sera and commercial ELISAs has resulted in a lot of information on only a few APPs. Disease is a threat to the poultry industry, as pathogens have the potential to evolve, spread and cause rapid onset of disease that is detrimental to the welfare of birds. Low level, sub-acute disease with non-specific, often undiagnosed causes can greatly affect bird health and growth and impact greatly on productivity and profitability. Developing and validating methods to measure and characterise APPs in chickens will allow these proteins to be used diagnostically for monitoring flock health. Using immune parameters such as APPs that correlate with disease resistance or improvements in production and welfare will allow the use of APPs as selection parameters for breeding to be evaluated. For APPs to be useful parameters on which to evaluate chicken health, information on normal APP concentrations is required. Ceruloplasmin (Cp) and PIT54 concentrations were found to be much lower in healthy birds form commercial production farms than the reported normal values obtained from the literature. These APPs were found to be significantly higher in culled birds from a commercial farm and Cp, PIT54 and ovotransferrin (Ovt) were significantly higher in birds classified as having obvious gait defects. Using quantitative shotgun proteomics to identify the differentially abundant proteins between three pools: highly acute phase (HAP), acute phase (AP) and non-acute phase (NAP), generated data from which a selection of proteins, based on the fold difference between the three pools was made. These proteins were targeted on a individual samples alongside proteins known to be APPs in chickens or other species: serum amyloid A (SAA), C-reactive protein (CRP), Ovt, apolipoprotein A-I (apo-AI), transthyretin (Ttn), haemopexin (Hpx) and PIT54. Together with immunoassay data for SAA, Ovt, alpha-1-acid glycoprotein (AGP) and Cp the results of this research reveal that SAA is the only major APP in chickens. Ovotransferrin and AGP behave as moderate APPs while PIT54 and Cp are minor APPs. Haemopexin was not significantly different between the three acute phase groups. Apolipoprotein AI and Ttn were significantly lower in the HAP and AP groups and as such can be classed as negative APPs. In an effort to identify CRP, multiple anti-sera cross reacting with CRP from other species were used and a phosphorylcholine column known to affinity purify CRP were used. Enriched fractions containing low molecular weight proteins, elutions from the affinity column together with HAP, AP and NAP pooled samples were applied to a Q-Exactive Hybrid Quadrupole–Orbitrap mass spectrometer (Thermo Scientific) for Shotgun analysis and CRP was not identified. It would appear that CRP is not present as a plasma protein constitutively or during an APR in chickens and as such is not an APP in this species. Of the proteins targeted as possible novel biomarkers of the APR in chickens mannan binding lectin associated serine protease-2, α-2-HS-glycoprotein (fetuin) and major facilitator superfamily domain-containing protein 10 were reduced in abundance in the HAP group, behaving as negative biomarkers. Myeloid protein and putative ISG(12)2 were positively associated with the acute phase being significantly higher in the HAP and AP groups. The protein cathepsin D was significantly higher in both HAP and AP compared to the NAP indicating that of all the proteins targeted, this appears to have the most potential as a biomarker of the acute phase, as it was significantly increased in the AP as well as the HAP group. To evaluate APPs and investigate biomarkers of intestinal health, a study using re-used poultry litter was undertaken. The introduction of litter at 12 days of age did not significantly increase any APPs measured using immunoassays and quantitative proteomics at 3, 6 and 10 days post introduction. While no APP was found to be significantly different between the challenged and control groups at anytime point, the APPs AGP, SAA and Hpx did increase over time in all birds. The protein apolipoprotein AIV (apo-AIV) was targeted as a possible APP and because of its reported role in controlling satiety. An ELISA was developed, successfully validated and used to measure apo-AIV in this study. While no significant differences in apo-AIV plasma concentrations between challenged and control groups were identified apo-AIV plasma concentrations did change significantly between certain time points in challenged and control groups. Apoliporotein AIV does not appear to behave as an APP in chickens, as it was not significantly different between acute phase groups. The actin associated proteins villin and gelsolin were investigated as possible biomarkers of intestinal health. Villin was found not to be present in the plasma of chickens and as such not a biomarker target. Gelsolin was found not to be differentially expressed during the acute phase or as a result of intestinal challenge. Finally a proteomic approach was undertaken to investigate gastrocnemius tendon (GT) rupture in broiler chickens with a view of elucidating to and identify proteins associated with risk of rupture. A number of proteins were found to be differentially expressed between tendon pools and further work would enable further detailing of these findings. In conclusion this work has made a number of novel findings and addressed a number of data poor areas. The area of chicken APPs research has stagnated over the last 15 years with publications becoming repetitive and reliant on a small number of immunoassays. This work has sought to characterise the classic APPs in chickens, and use a quantitative proteomic approach to measure and categorise them. This method was also used to take a fresh approach to biomarker identification for both the APR and intestinal health. The development and validation of assays for Ovt and apo-AIV and the shotgun data mean that these proteins can be further characterised in chickens with a view of applying their measurement to diagnostics and selective breeding programs.