Surveillance Study of Klebsiella pneumoniae in the Giant Panda Revealed High Genetic Diversity and Antibiotic Therapy Challenge

Klebsiella pneumoniae is not only a worldwide human pathogen, it also effects wildlife, such as the giant panda (Ailuropoda melanoleuca), in which it has recently been evidenced to result in diarrhea, organ failure, and even death. A K. pneumoniae investigation was carried out at the Chengdu Research Base of Giant Panda Breeding in 2018. As part of the investigation, the pulsed-field gel electrophoresis (PFGE) typing, multilocus-sequence typing (MLST), antibiotic resistance profiles (ARPs), and antibiotic resistance genes (ARGs) were studied based on all isolates. Fecal samples were collected from 72 A. melanoleuca from May to December 2018, and a total of 90 K. pneumoniae were isolated from 153 fecal samples. The genotyping results showed that the isolates had high diversity, of which 84 clusters were obtained by PFGE and 57 STs by MLST. The overall trend of the similarity of isolates was the first sample period > second sample period > third sample period, which showed the increasement of genome variability of K. pneumoniae. In addition, 90 isolates showed high resistance to ampicillin, rifampicin, and compound sulfamethoxazole. Of the obtained isolates, 50% carried 6~8 ARPs, and the carrying volume increased during three sample periods, in which we found two isolates carrying 12 and 13 ARPs during the third sample period, respectively. Moreover, a total of 65 ARGs were detected (90.28%, 65/72) in 90 K. pneumoniae samples. Almost all bacteria sampled contained 17 ARGs that belonged to the β-lactamase, Multidrug, MGEs, Aminoglycoside, and Tetracycline, which may be the basis of ARPs of K. pneumoniae. Moreover, the types of Multidrug and MGEs had a greater impact on antibiotic susceptivity of K. pneumoniae. Our results showed that K. pneumoniae has a serious risk of transmission in A. melanoleuca and K. pneumoniae had a high possibility of genome diversity and the risk of drugs tolerance under the large antibiotic usage.

Skin Mycobiota of the Captive Giant Panda (Ailuropoda melanoleuca) and the Distribution of Opportunistic Dermatomycosis-Associated Fungi in Different Seasons

Dermatomycosis is the second major cause of morbidity in giant pandas (Ailuropoda melanoleuca), and seriously endangers its health. Previous observations indicated that the occurrence of dermatomycosis in the giant panda varies in different seasons. The skin microbiota is a complex ecosystem, but knowledge on the community structure and the pathogenic potentials of fungi on the skin of the giant panda remains limited. In this study, samples from the giant panda skin in different seasons were collected, and the mycobiota were profiled by 18S rRNA gene sequencing. In total, 375 genera in 38 phyla were detected, with Ascomycota, Basidiomycota, Streptophyta, and Chlorophyta as the predominant phyla and Trichosporon, Guehomyces, Davidiella, Chlorella, Asterotremella, and Klebsormidium as the predominant genera. The skin mycobiota of the giant panda changed in the seasons, and the diversity and abundance of the skin fungi were significantly higher in spring, autumn, and summer than in the winter. Several dermatomycosis-associated fungi were detected as opportunists in the skin mycobiota of healthy giant pandas. Clinical dermatomycosis in the giant panda is observed more in summer and autumn. In this study, the results indicated that the high diversity and abundance of the skin fungi may have enhanced the occurrence of dermatomycosis in autumn and summer, and that dermatomycosis-associated fungi are the normal components of the skin mycobiota.

Skin Microbiota of the Captive Giant Panda (Ailuropoda Melanoleuca) and the Distribution of Opportunistic Skin Disease-Associated Bacteria in Different Seasons

The giant panda is one of the rarest animals in the world. Skin diseases seriously endanger the health of giant panda and are considered the second major cause of its morbidity. Skin microbiota is a complex ecosystem, and the community structure and the pathogenic potential of bacteria on giant panda skin remain largely unclear. In order to understand the skin bacterial flora of captive giant pandas, the microbiota in giant panda skin samples collected during different seasons was profiled via 16S rRNA gene sequencing. In total, 522 genera from 53 bacterial phyla were detected, with Proteobacteria (40.5%), Actinobacteria (23.1%), Firmicutes (21.1%), Bacteroidetes (9.5%), Cyanobacteria (2.1%), and Thermi (1.2%) as the predominant phyla and Streptococcus (13.9%), Acinetobacter (9.2%), Staphylococcus (2.9%), Pseudomonas (5.9%), Dermacoccus (4.8%), Brachybacterium (2.9%), Escherichia (2.7%), Chryseobacterium (2.1%), Arthrobacter (1.6%), Kocuria (1.5%), Psychrobacter (1.2%), Deinococcus (1.1%), and Flavobacterium (1.1%) as the predominant genera. The results indicated that the diversity was lower in winter than in other seasons and higher in autumn than in other seasons, and the abundance in spring was significantly higher than that in other seasons. Several skin disease-associated bacteria were detected as opportunists in the skin microbiota of healthy giant pandas. In this study, the results indicated that the high diversity and abundance of the skin bacteria may have enhanced the occurrence of skin disease in autumn and spring and that skin disease-associated bacteria are the normal components of the skin microbiota.

Laterality in Responses to Acoustic Stimuli in Giant Pandas

Simple Summary

Functional lateralization in the auditory system has been widely studied. Accordingly, behavioral laterality responses affected by acoustic stimuli have been observed in many vertebrate species. In this study, we assessed giant pandas’ behavioral responses to different acoustic stimuli in order to examine cerebral lateralization. We concluded that adult giant pandas showed a left-hemisphere bias in response to positive acoustic stimuli. Furthermore, we found the specific valence of cerebral lateralization for different categories of acoustic stimuli, of which some were relevant to the lateralization while others were not relevant. Our findings support an evolutionary strategy that giant pandas process auditory signals similar to other mammals.

Abstract

Cerebral lateralization is a common feature present in many vertebrates and is often observed in response to various sensory stimuli. Numerous studies have proposed that some vertebrate species have a right hemisphere or left hemisphere dominance in response to specific types of acoustic stimuli. We investigated lateralization of eight giant pandas (Ailuropoda melanoleuca) by using a head turning paradigm and twenty-eight acoustic stimuli with different emotional valences which included twenty-four conspecific and four non-conspecific acoustic stimuli (white noise, thunder, and vocalization of a predator). There was no significant difference in auditory laterality in responses to conspecific or non-conspecific sounds. However, the left cerebral hemisphere processed the positive stimuli, whereas neither of the two hemispheres exhibited a preference for processing the negative stimuli. Furthermore, the right hemisphere was faster than the left hemisphere in processing emotional stimuli and conspecific stimuli. These findings demonstrate that giant pandas exhibit lateralization in response to different acoustic stimuli, which provides evidence of hemispheric asymmetry in this species.

Modeling activity patterns of wildlife using time-series analysis

The study of wildlife activity patterns is an effective approach to understanding fundamental ecological and evolutionary processes. However, traditional statistical approaches used to conduct quantitative analysis have thus far had limited success in revealing underlying mechanisms driving activity patterns. Here, we combine wavelet analysis, a type of frequency‐based time‐series analysis, with high‐resolution activity data from accelerometers embedded in GPS collars to explore the effects of internal states (e.g., pregnancy) and external factors (e.g., seasonal dynamics of resources and weather) on activity patterns of the endangered giant panda (Ailuropoda melanoleuca). Giant pandas exhibited higher frequency cycles during the winter when resources (e.g., water and forage) were relatively poor, as well as during spring, which includes the giant panda's mating season. During the summer and autumn when resources were abundant, pandas exhibited a regular activity pattern with activity peaks every 24 hr. A pregnant individual showed distinct differences in her activity pattern from other giant pandas for several months following parturition. These results indicate that animals adjust activity cycles to adapt to seasonal variation of the resources and unique physiological periods. Wavelet coherency analysis also verified the synchronization of giant panda activity level with air temperature and solar radiation at the 24‐hr band. Our study also shows that wavelet analysis is an effective tool for analyzing high‐resolution activity pattern data and its relationship to internal and external states, an approach that has the potential to inform wildlife conservation and management across species.