African trypanosomes thrive in the bloodstream and tissue spaces of a wide range of mammalian hosts. Infections of cattle cause an enormous socio-economic burden in sub-Saharan Africa. A hallmark of the trypanosome lifestyle is the flagellate’s incessant motion. This work details the cell motility behavior of the four livestock-parasites Trypanosoma vivax, T. brucei, T. evansi and T. congolense. The trypanosomes feature distinct swimming patterns, speeds and flagellar wave frequencies, although the basic mechanism of flagellar propulsion is conserved, as is shown by extended single flagellar beat analyses. Three-dimensional analyses of the trypanosomes expose a high degree of dynamic pleomorphism, typified by the ‘cellular waveform’. This is a product of the flagellar oscillation, the chirality of the flagellum attachment and the stiffness of the trypanosome cell body. The waveforms are characteristic for each trypanosome species and are influenced by changes of the microenvironment, such as differences in viscosity and the presence of confining obstacles. The distinct cellular waveforms may be reflective of the actual anatomical niches the parasites populate within their mammalian host. T. vivax displays waveforms optimally aligned to the topology of the bloodstream, while the two subspecies T. brucei and T. evansi feature distinct cellular waveforms, both additionally adapted to motion in more confined environments such as tissue spaces. T. congolense reveals a small and stiff waveform, which makes these parasites weak swimmers and destined for cell adherence in low flow areas of the circulation. Thus, our experiments show that the differential dissemination and annidation of trypanosomes in their mammalian hosts may depend on the distinct swimming capabilities of the parasites.

Tsetse flies undergo drastic fluctuations in their water content throughout their adult life history due to events such as blood feeding, dehydration and lactation, an essential feature of the viviparous reproductive biology of tsetse. Aquaporins (AQPs) are transmembrane proteins that allow water and other solutes to permeate through cellular membranes. Here we identify tsetse aquaporin (AQP) genes, examine their expression patterns under different physiological conditions (blood feeding, lactation and stress response) and perform functional analysis of three specific genes utilizing RNA interference (RNAi) gene silencing. Ten putative aquaporins were identified in the Glossina morsitans morsitans (Gmm) genome, two more than has been previously documented in any other insect. All organs, tissues, and body parts examined had distinct AQP expression patterns. Two AQP genes, gmmdripa and gmmdripb ( = gmmaqp1a and gmmaqp1b) are highly expressed in the milk gland/fat body tissues. The whole-body transcript levels of these two genes vary over the course of pregnancy. A set of three AQPs (gmmaqp5, gmmaqp2a, and gmmaqp4b) are expressed highly in the Malpighian tubules. Knockdown of gmmdripa and gmmdripb reduced the efficiency of water loss following a blood meal, increased dehydration tolerance and reduced heat tolerance of adult females. Knockdown of gmmdripa extended pregnancy length, and gmmdripb knockdown resulted in extended pregnancy duration and reduced progeny production. We found that knockdown of AQPs increased tsetse milk osmolality and reduced the water content in developing larva. Combined knockdown of gmmdripa, gmmdripb and gmmaqp5 extended pregnancy by 4–6 d, reduced pupal production by nearly 50%, increased milk osmolality by 20–25% and led to dehydration of feeding larvae. Based on these results, we conclude that gmmDripA and gmmDripB are critical for diuresis, stress tolerance and intrauterine lactation through the regulation of water and/or other uncharged solutes.

Reliable molecular identification of vertebrate species from morphologically unidentifiable tissue is critical for the prosecution of illegally-traded wildlife products, conservation-based biodiversity research, and identification of blood-meal hosts of hematophagous invertebrates. However, forensic identification of vertebrate tissue relies on sequencing of the mitochondrial cytochrome oxidase I (COI) 'barcode' gene, which remains costly for purposes of screening large numbers of unknown samples during routine surveillance. Here, we adapted a rapid, low-cost approach to differentiate 10 domestic and 24 wildlife species that are common in the East African illegal wildlife products trade based on their unique high-resolution melting profiles from COI, cytochrome b, and 16S ribosomal RNA gene PCR products. Using the approach, we identified (i) giraffe among covertly sampled meat from Kenyan butcheries, and (ii) forest elephant mitochondrial sequences among savannah elephant reference samples. This approach is being adopted for high-throughput pre-screening of potential bushmeat samples in East African forensic science pipelines. Unsustainable hunting, consumption, and sale of bushmeat in Africa contribute immensely to the decline of threatened wild animal species. The global bushmeat trade is valued at several billion US dollars. Up to 270 tons of bushmeat were flown into Europe through a single airport in 2010 from Africa 1. While this is a major crisis for wildlife in central and western Africa, it is a growing concern in eastern and southern Africa 2. Efforts to regulate or prevent illegal wildlife trade depends on accurate, efficient, and sustainable tools for species identification of confiscated and surveillance samples. Illegal wildlife trade is mainly fuelled by the need for diet and income supplementation 3. The consequences of direct human contact with bushmeat have been severe. A classic example of disease originating from or harboured by bushmeat is Ebola virus disease, which has infected humans upon contact with infected wild animals such as fruit bats, nonhuman primates, and forest antelopes 4,5. The impact of bushmeat hunting on animal populations can also be severe 6. Many favoured wild animal species for bushmeat are already endangered, some close to extinction 7. There are also flow-on effects to the ecosystems 8 and tourism.