Low-cost molecular methods to characterise gastrointestinal nematode co-infections of goats in Africa

Background
Veterinary diagnostics aid intervention strategies, track zoonoses, and direct selective breeding programs in livestock. In ruminants, gastrointestinal nematode (GIN) parasites are a major cause of production losses, but morphologically similar species limit our understanding of how specific GIN co‑infections impact health in resource‑limited settings. To estimate the presence and relative abundance of GINs and other helminths at the spe‑cies level, we sought to develop a low‑cost and low‑resource molecular toolkit applied to goats from rural Malawi smallholdings.
Methods
Goats were subjected to health scoring and faecal sampling on smallholdings in Lilongwe district, Malawi. Infection intensities were estimated by faecal nematode egg counts with a faecal subsample desiccated for DNA analysis. Two DNA extraction methods were tested (low‑resource magbead kit vs high‑resource spin‑column kit), with resulting DNA screened by endpoint polymerase chain reaction (PCR), semi‑quantitative PCR, quantitative PCR (qPCR), high‑resolution melt curve analysis (HRMC), and ‘nemabiome’ internal transcribed spacer 2 (ITS‑2) amplicon sequencing.
Results
Both DNA isolation methods yielded comparable results despite poorer DNA purity and faecal contaminant carryover from the low‑resource magbead method. GINs were detected in 100% of samples regardless of infection intensity. Co‑infections with GINs and coccidia (Eimeria spp.) were present in most goats, with GIN populations domi‑nated by Haemonchus contortus, Trichostrongylus colubriformis, Trichostrongylus axei, and Oesophagostomum columbi-anum. Both multiplex PCR and qPCR were highly predictive of GIN species proportions obtained using nemabiome amplicon sequencing; however, HRMC was less reliable than PCR in predicting the presence of particular species.
Conclusions
These data represent the first ‘nemabiome’ sequencing of GINs from naturally infected smallholder goats in Africa and show the variable nature of GIN co‑infections between individual animals. A similar level of granu‑larity was detected by semi‑quantitative PCR methods, which provided an accurate summary of species composition.Assessing GIN co‑infections is therefore possible using cost‑efficient low‑resource DNA extraction and PCR approaches that can increase the capacity of molecular resources in areas where sequencing platforms are not availa‑ble; and also open the door to affordable molecular GIN diagnostics. Given the diverse nature of infections in livestock and wildlife, these approaches have potential for disease surveillance in other areas.