Unnatural diet composition and frequent feeding regimes may play an aetiological role in the multiple diseases prevalent in captive cheetahs. This study investigated the responses of captive-born (hand-reared) cheetahs (n = 6) to a reduced feeding frequency schedule distinguished by offering larger quantities of food less frequently. The study cheetahs were fed four once-daily meals per week during the 3-week treatment period, followed by a 3-week control period in which they were fed two daily rations six days a week. Total weekly food intake was maintained throughout the study. Variations in behaviour, faecal consistency score (FCS), and faecal glucocorticoid metabolite concentration were measured. Less frequent feeding resulted in higher FCS (p < 0.01) and locomotory behaviour (p < 0.05) among the studied cheetahs. Faecal glucocorticoid metabolite concentration demonstrated an initial acute stress response to the change in feeding frequency (p < 0.05) and subsequent adaptation. The results of the FCS analysis suggest that the more natural feeding pattern could have benefited the studied cheetahs\' gastrointestinal health without a significant behavioural or physiological stress response overall to the change in feeding frequency.

Herein, we describe the management of nasopharyngitis caused by Schizophyllum commune infection in a captive cheetah. Computed tomography revealed a nodule in the nasal cavity and pharynx, and an endoscopic biopsy was performed. As a result, the nodule was surgically resected because of a suspected carcinoma. However, the surgical specimen was histologically re-evaluated and a fungal granuloma was diagnosed. Sequence analysis of DNA from formalin-fixed, paraffin-embedded samples revealed S. commune infection. The cheetah was administered fluconazole orally for 73 days. However, the drug was ineffective and itraconazole was administered for 14 days. Symptoms such as nasal discharge and sneezing have completely resolved for 4 years.

African large carnivores have undergone significant range and population declines over recent decades. Although conservation planning and the management of threatened species requires accurate assessments of population status and monitoring of trends, there is evidence that biodiversity monitoring may not be evenly distributed or occurring where most needed. Here, we provide the first systematic review of African large carnivore population assessments published over the last two decades (2000-2020), to investigate trends in research effort and identify knowledge gaps. We used generalised linear models (GLMs) and generalised linear mixed models (GLMMs) to identify taxonomic and geographical biases, and investigated biases associated with land use type and author nationality. Research effort was significantly biased towards lion (Panthera leo) and against striped hyaena (Hyaena hyaena), despite the latter being the species with the widest continental range. African wild dog (Lycaon pictus) also exhibited a negative bias in research attention, although this was partly explained by its relatively restricted distribution. The number of country assessments for a species was significantly positively associated with its geographic range in that country. Population assessments were biased towards southern and eastern Africa, particularly South Africa and Kenya. Northern, western, and central Africa were generally under-represented. Most studies were carried out in photographic tourism protected areas under government management, while non-protected and trophy hunting areas received less attention. Outside South Africa, almost half of studies (41%) did not include authors from the study country, suggesting that significant opportunities exist for capacity building in range states. Overall, large parts of Africa remain under-represented in the literature, and opportunities exist for further research on most species and in most countries. We develop recommendations for actions aimed at overcoming the identified biases and provide researchers, practitioners, and policymakers with priorities to help inform future research and monitoring agendas.

Fecal proteomics allows for the identification of proteins and peptides present in stools and is useful in finding possible new biomarkers for diagnosing and/or monitoring gastrointestinal (GI) disorders. In the present study, we investigated the fecal proteome in healthy and diseased cheetahs (Acinonyx jubatus). Captive individuals of this species frequently show gastrointestinal disorders characterized by recurrent episodes of diarrhea, rare episodes of vomiting and weight loss, associated with Helicobacter spp. infection. Fecal proteomic evaluation has been performed by two-dimensional electrophoresis followed by liquid chromatography-tandem mass spectrometry. In healthy cheetahs, the results showed the presence of the following proteins: collagen alpha-1 (II) chain, transthyretin, IgG Fc-binding protein, titin, dystonin, isopentenyl-diphosphate Delta-isomerase 1, sodium/potassium-transporting ATPase subunit alpha-1 and protein disulfide-isomerase A6. The presence of albumin isoforms was found only in diseased cheetahs. The present paper reports the study of the fecal proteome in the cheetah, evidences some differences between healthy and diseased patients and confirms, once again, the potential of fecal proteomics for the study of the GI environment, with promising developments regarding the identification of new diagnostic/monitoring markers.

We live in a world characterized by biodiversity loss and global environmental change. The extinction of large carnivores can have ramifying effects on ecosystems like an uncontrolled increase in wild herbivores, which in turn can have knock-on impacts on vegetation regeneration and communities. Cheetahs (Acinonyx jubatus) serve important ecosystem functions as apex predators; yet, they are quickly heading towards an uncertain future. Threatened by habitat loss, human-wildlife conflict and illegal trafficking, there are only approximately 7100 individuals remaining in nature. We present the most comprehensive genome-wide analysis of cheetah phylogeography and conservation genomics to date, assembling samples from nearly the entire current and past species\' range. We show that their phylogeography is more complex than previously thought, and that East African cheetahs (A. j. raineyi) are genetically distinct from Southern African individuals (A. j. jubatus), warranting their recognition as a distinct subspecies. We found strong genetic differentiation between all classically recognized subspecies, thus refuting earlier findings that cheetahs show only little differentiation. The strongest differentiation was observed between the Asiatic and all the African subspecies. We detected high inbreeding in the Critically Endangered Iranian (A. j. venaticus) and North-western (A. j. hecki) subspecies, and show that overall cheetahs, along with snow leopards, have the lowest genome-wide heterozygosity of all the big cats. This further emphasizes the cheetah\'s perilous conservation status. Our results provide novel and important information on cheetah phylogeography that can support evidence-based conservation policy decisions to help protect this species. This is especially relevant in light of ongoing and proposed translocations across subspecies boundaries, and the increasing threats of illegal trafficking.

Cheetahs are the fastest land animal. Their galloping shows three characteristics: small vertical movement of their center of mass, small whole-body pitching movement, and large spine bending movement. We hypothesize that these characteristics lead to enhanced gait performance in cheetahs, including higher gait speed. In this study, we used a simple model with a spine joint and torsional spring, which emulate the body flexibility, to verify our hypothesis from a dynamic perspective. Specifically, we numerically searched periodic solutions and evaluated what extent each solution shows the three characteristics. We then evaluated the gait performance and found that the solutions with the characteristics achieve high performances. This result supports our hypothesis. Furthermore, we revealed the mechanism for the high performances through the dynamics of the spine movement. These findings extend the current understanding of the dynamic mechanisms underlying high-speed locomotion in cheetahs.

Feline herpesvirus type 1 (FHV-1) is endemic in captive cheetahs and sporadically causes devastating disease. Modified live vaccines (MLV), intended for use in domestic cats, are used in some captive cheetah populations and have been anecdotally linked to disease in certain subpopulations. Ten FHV-1 isolates from ten captive cheetahs and one isolate from an MLV used to inoculate four of the host animals were analyzed. Viral DNA was extracted for full-genome sequencing by Illumina MiSeq with viral genomes then used for phylogenomic and recombinational analyses. The FHV-1 shed by vaccinated cheetahs were almost identical to the MLV, with few variants among viral genomes. Eight cheetah FHV-1 isolates and the MLV were grouped in a clade along with FHV-1 isolates from domestic cats in the USA. The remaining two cheetah FHV-1 isolates (unknown host vaccine status) were not associated with a clade. The likely ancestral origin of these two isolates involves recombination events between Australian domestic cat and cheetah FHV-1 isolates. Collectively, these data suggest that the MLV is capable of causing clinical disease and viral shedding in some cheetahs and represents evidence of interspecies transmission of virus between domestic and wild cats.

BACKGROUND: Extracellular recording represents a crucial electrophysiological technique in neuroscience for studying the activity of single neurons and neuronal populations. The electrodes capture voltage traces that, with the help of analytical tools, reveal action potentials (\'spikes\') as well as local field potentials. The process of spike sorting is used for the extraction of action potentials generated by individual neurons. Until recently, spike sorting was performed with manual techniques, which are laborious and unreliable due to inherent operator bias. As neuroscientists add multiple electrodes to their probes, the high-density devices can record hundreds to thousands of neurons simultaneously, making the manual spike sorting process increasingly difficult. The advent of automated spike sorting software has offered a compelling solution to this issue and, in this study, we present a simple-to-execute framework for running an automated spike sorter.
METHODS: Tetrode recordings of freely-moving mice are obtained from the CA1 region of the hippocampus as they navigate a linear track. Tetrode recordings are also acquired from the prelimbic cortex, a region of the medial prefrontal cortex, while the mice are tested in a T maze. All animals are implanted with custom-designed, 3D-printed microdrives that carry 16 electrodes, which are bundled in a 4-tetrode geometry.
RESULTS: We provide an overview of a framework for analyzing single-unit data in which we have concatenated the acquisition system (Cheetah, Neuralynx) with analytical software (MATLAB) and an automated spike sorting pipeline (MountainSort). We give precise instructions on how to implement the different steps of the framework, as well as explanations of our design logic. We validate this framework by comparing manually-sorted spikes against automatically-sorted spikes, using neural recordings of the hippocampus and prelimbic cortex in freely-moving mice.
CONCLUSIONS: We have efficiently integrated the MountainSort spike sorter with Neuralynx-acquired neural recordings. Our framework is easy to implement and provides a high-throughput solution. We predict that within the broad field of bioelectronic medicine, those teams that incorporate high-density neural recording devices to their armamentarium might find our framework quite valuable as they expand their analytical footprint.

Anthrax is a bacterial disease caused by Bacillus anthracis that affects wildlife, livestock and also humans in different parts of the world. It is endemic in some parts of Africa, including Namibia, with species differing in their susceptibility to the disease. Carnivores are typically less susceptible to anthrax than herbivores. Most carnivore species survive infection and have high seroprevalence against anthrax, whereas most herbivore species have low seroprevalence and typically die quickly when infected. Several reports have shown that cheetahs, unlike most other large carnivores, are susceptible to anthrax leading to a sudden death. This finding was suggested to be linked to the low genetic variability of cheetahs which might reduce an adequate immune response and thus explain such a high susceptibility to the disease. Here, we report an incidence of three free-ranging cheetahs that died within 24 h after feeding on a mountain zebra that tested positive for anthrax in the Namib Desert. We were able to reconstruct this incidence with the data recorded in the GPS (Global Positioning System) collar worn by one of the cheetahs and retrieved in the field. It is very likely that the cheetahs died from anthrax, although Bacillus anthracis could not be isolated from tissue and soil samples by bacterial culturing. The mountain zebra is the first described case of a wild animal that tested positive for anthrax in this arid area in southwestern of Namibia. We discuss the negative laboratory results of the cheetahs in the light of new insights of their immune system and its potential to mount a response against this bacteria.

Behavioural studies of elusive wildlife species are challenging but important when they are threatened and involved in human-wildlife conflicts. Accelerometers (ACCs) and supervised machine learning algorithms (MLAs) are valuable tools to remotely determine behaviours. Here we used five captive cheetahs in Namibia to test the applicability of ACC data in identifying six behaviours by using six MLAs on data we ground-truthed by direct observations. We included two ensemble learning approaches and a probability threshold to improve prediction accuracy. We used the model to then identify the behaviours in four free-ranging cheetah males. Feeding behaviours identified by the model and matched with corresponding GPS clusters were verified with previously identified kill sites in the field. The MLAs and the two ensemble learning approaches in the captive cheetahs achieved precision (recall) ranging from 80.1% to 100.0% (87.3% to 99.2%) for resting, walking and trotting/running behaviour, from 74.4% to 81.6% (54.8% and 82.4%) for feeding behaviour and from 0.0% to 97.1% (0.0% and 56.2%) for drinking and grooming behaviour. The model application to the ACC data of the free-ranging cheetahs successfully identified all nine kill sites and 17 of the 18 feeding events of the two brother groups. We demonstrated that our behavioural model reliably detects feeding events of free-ranging cheetahs. This has useful applications for the determination of cheetah kill sites and helping to mitigate human-cheetah conflicts.