Current Issue

2023 Vol. 44, No. 6

Targeting key enzymes that generate oxalate precursors or substrates is an alternative strategy to eliminate primary hyperoxaluria type I (PH1), the most common and life-threatening type of primary hyperoxaluria. The compact Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) from the Prevotella and Francisella 1 (Cpf1) protein simplifies multiplex gene editing and allows for all-in-one adeno-associated virus (AAV) delivery. We hypothesized that the multiplex capabilities of the Cpf1 system could help minimize oxalate formation in PH1 by simultaneously targeting the hepatic hydroxyacid oxidase 1 (Hao1) and lactate dehydrogenase A (Ldha) genes. Study cohorts included treated PH1 rats (AgxtQ84X rats injected with AAV-AsCpf1 at 7 days of age), phosphate-buffered saline (PBS)-injected PH1 rats, untreated PH1 rats, and age-matched wild-type (WT) rats. The most efficient and specific CRISPR RNA (crRNA) pairs targeting the rat Hao1 and Ldha genes were initially screened ex vivo. In vivo experiments demonstrated efficient genome editing of the Hao1 and Ldha genes, primarily resulting in small deletions. This resulted in decreased transcription and translational expression of Hao1 and Ldha. Treatment significantly reduced urine oxalate levels, reduced kidney damage, and alleviated nephrocalcinosis in rats with PH1. No liver toxicity, ex-liver genome editing, or obvious off-target effects were detected. We demonstrated the AAV-AsCpf1 system can target multiple genes and rescue the pathogenic phenotype in PH1, serving as a proof-of-concept for the development of multiplex genome editing-based gene therapy.
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection can result in more severe syndromes and poorer outcomes in patients with diabetes and obesity. However, the precise mechanisms responsible for the combined impact of coronavirus disease 2019 (COVID-19) and diabetes have not yet been elucidated, and effective treatment options for SARS-CoV-2-infected diabetic patients remain limited. To investigate the disease pathogenesis, K18-hACE2 transgenic (hACE2Tg) mice with a leptin receptor deficiency (hACE2-Lepr-/-) and high-fat diet (hACE2-HFD) background were generated. The two mouse models were intranasally infected with a 5×105 median tissue culture infectious dose (TCID50) of SARS-CoV-2, with serum and lung tissue samples collected at 3 days post-infection. The hACE2-Lepr-/- mice were then administered a combination of low-molecular-weight heparin (LMWH) (1 mg/kg or 5 mg/kg) and insulin via subcutaneous injection prior to intranasal infection with 1×104 TCID50 of SARS-CoV-2. Daily drug administration continued until the euthanasia of the mice. Analyses of viral RNA loads, histopathological changes in lung tissue, and inflammation factors were conducted. Results demonstrated similar SARS-CoV-2 susceptibility in hACE2Tg mice under both lean (chow diet) and obese (HFD) conditions. However, compared to the hACE2-Lepr+/+ mice, hACE2-Lepr-/- mice exhibited more severe lung injury, enhanced expression of inflammatory cytokines and hypoxia-inducible factor-1α (HIF-1α), and increased apoptosis. Moreover, combined LMWH and insulin treatment effectively reduced disease progression and severity, attenuated lung pathological changes, and mitigated inflammatory responses. In conclusion, pre-existing diabetes can lead to more severe lung damage upon SARS-CoV-2 infection, and LMWH may be a valuable therapeutic approach for managing COVID-19 patients with diabetes.
Following the outbreak of coronavirus disease 2019 (COVID-19), several severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-related coronaviruses have been discovered. Previous research has identified a novel lineage of SARS-CoV-2-related CoVs in bats, including RsYN04, which recognizes human angiotensin-converting enzyme 2 (ACE2) and thus poses a potential threat to humans. Here, we screened the binding of the RsYN04 receptor-binding domain (RBD) to ACE2 orthologs from 52 animal species and found that the virus showed a narrower ACE2-binding spectrum than SARS-CoV-2. However, the presence of the T484W mutation in the RsYN04 RBD broadened its range. We also evaluated 44 SARS-CoV-2 antibodies targeting seven epitope communities in the SARS-CoV-2 RBD, together with serum obtained from COVID-19 convalescents and vaccinees, to determine their cross-reaction against RsYN04. Results showed that no antibodies, except for the RBD-6 and RBD-7 classes, bound to the RsYN04 RBD, indicating substantial immune differences from SARS-CoV-2. Furthermore, the structure of the RsYN04 RBD in complex with cross-reactive antibody S43 in RBD-7 revealed a potently broad epitope for the development of therapeutics and vaccines. Our findings suggest RsYN04 and other viruses belonging to the same clade have the potential to infect several species, including humans, highlighting the necessity for viral surveillance and development of broad anti-coronavirus countermeasures.
Quantification of behaviors in macaques provides crucial support for various scientific disciplines, including pharmacology, neuroscience, and ethology. Despite recent advancements in the analysis of macaque behavior, research on multi-label behavior detection in socially housed macaques, including consideration of interactions among them, remains scarce. Given the lack of relevant approaches and datasets, we developed the Behavior-Aware Relation Network (BARN) for multi-label behavior detection of socially housed macaques. Our approach models the relationship of behavioral similarity between macaques, guided by a behavior-aware module and novel behavior classifier, which is suitable for multi-label classification. We also constructed a behavior dataset of rhesus macaques using ordinary RGB cameras mounted outside their cages. The dataset included 65 913 labels for 19 behaviors and 60 367 proposals, including identities and locations of the macaques. Experimental results showed that BARN significantly improved the baseline SlowFast network and outperformed existing relation networks. In conclusion, we successfully achieved multi-label behavior detection of socially housed macaques with both economic efficiency and high accuracy.
We describe a unique new species and genus of agamid lizard from the karstic massifs of Khammouan Province, central Laos. Laodracon carsticola Gen. et sp. nov. is an elusive medium-sized lizard (maximum snout-vent length 101 mm) specifically adapted to life on limestone rocks and pinnacles. To assess the phylogenetic position of the new genus amongst other agamids, we generated DNA sequences from two mitochondrial gene fragments (16S rRNA and ND2) and three nuclear loci (BDNF, RAG1 and c-mos), with a final alignment comprising 7 418 base pairs for 64 agamid species. Phylogenetic analyses unambiguously place the new genus in the mainland Asia subfamily Draconinae, where it forms a clade sister to the genus Diploderma from East Asia and the northern part of Southeast Asia. Morphologically, the new genus is distinguished from all other genera in Draconinae by possessing a notably swollen tail base with enlarged scales on its dorsal and ventral surfaces. Our work provides further evidence that limestone regions of Indochina represent unique “arks of biodiversity” and harbor numerous relict lineages. To date, Laodracon carsticola Gen. et sp. nov. is known from only two adult male specimens and its distribution seems to be restricted to a narrow limestone massif on the border of Khammouan and Bolikhamxai provinces of Laos. Additional studies are required to understand its life history, distribution, and conservation status.
Widespread species that inhabit diverse environments possess large population sizes and exhibit a high capacity for environmental adaptation, thus enabling range expansion. In contrast, narrow-range species are confined to restricted geographical areas and are ecologically adapted to narrow environmental conditions, thus limiting their ability to expand into novel environments. However, the genomic mechanisms underlying the differentiation between closely related species with varying distribution ranges remain poorly understood. The Niviventer niviventer species complex (NNSC), consisting of highly abundant wild rats in Southeast Asia and China, offers an excellent opportunity to investigate these questions due to the presence of both widespread and narrow-range species that are phylogenetically closely related. In the present study, we combined ecological niche modeling with phylogenetic analysis, which suggested that sister species cannot be both widespread and dominant within the same geographical region. Moreover, by assessing heterozygosity, linkage disequilibrium decay, and Tajima’s D analysis, we found that widespread species exhibited higher genetic diversity than narrow-range species. In addition, by exploring the “genomic islands of speciation”, we identified 13 genes in highly divergent regions that were shared by the two widespread species, distinguishing them from their narrow-range counterparts. Functional annotation analysis indicated that these genes are involved in nervous system development and regulation. The adaptive evolution of these genes likely played an important role in the speciation of these widespread species.
The timing of mammalian diversification in relation to the Cretaceous-Paleogene (KPg) mass extinction continues to be a subject of substantial debate. Previous studies have either focused on limited taxonomic samples with available whole-genome data or relied on short sequence alignments coupled with extensive species samples. In the present study, we improved an existing dataset from the landmark study of Meredith et al. (2011) by filling in missing fragments and further generated another dataset containing 120 taxa and 98 exonic markers. Using these two datasets, we then constructed phylogenies for extant mammalian families, providing improved resolution of many conflicting relationships. Moreover, the timetrees generated, which were calibrated using appropriate molecular clock models and multiple fossil records, indicated that the interordinal diversification of placental mammals initiated before the Late Cretaceous period. Additionally, intraordinal diversification of both extant placental and marsupial lineages accelerated after the KPg boundary, supporting the hypothesis that the availability of numerous vacant ecological niches subsequent to the mass extinction event facilitated rapid diversification. Thus, our results support a scenario of placental radiation characterized by both basal cladogenesis and active interordinal divergences spanning from the Late Cretaceous into the Paleogene.
Tree shrews (Tupaia belangeri chinensis) share a close relationship to primates and have been widely used in biomedical research. We previously established a spermatogonial stem cell (SSC)-based gene editing platform to generate transgenic tree shrews. However, the influences of long-term expansion on tree shrew SSC spermatogenesis potential remain unclear. Here, we examined the in vivo spermatogenesis potential of tree shrew SSCs cultured across different passages. We found that SSCs lost spermatogenesis ability after long-term expansion (>50 passages), as indicated by the failure to colonize the seminiferous epithelium and generate donor spermatogonia (SPG)-derived spermatocytes or spermatids marking spermatogenesis. RNA sequencing (RNA-seq) analysis of undifferentiated SPGs across different passages revealed significant gene expression changes after sub-culturing primary SPG lines for more than 40 passages on feeder layers. Specifically, DNA damage response and repair genes (e.g., MRE11, SMC3, BLM, and GEN1) were down-regulated, whereas genes associated with mitochondrial function (e.g., NDUFA9, NDUFA8, NDUFA13, and NDUFB8) were up-regulated after expansion. The DNA damage accumulation and mitochondrial dysfunction were experimentally validated in high-passage cells. Supplementation with nicotinamide adenine dinucleotide (NAD+) precursor nicotinamide riboside (NR) exhibited beneficial effects by reducing DNA damage accumulation and mitochondrial dysfunction in SPG elicited by long-term culture. Our research presents a comprehensive analysis of the genetic and physiological attributes critical for the sustained expansion of undifferentiated SSCs in tree shrews and proposes an effective strategy for extended in vitro maintenance.
The recalcitrance of pathogens to traditional antibiotics has made treating and eradicating bacterial infections more difficult. In this regard, developing new antimicrobial agents to combat antibiotic-resistant strains has become a top priority. Antimicrobial peptides (AMPs), a ubiquitous class of naturally occurring compounds with broad-spectrum antipathogenic activity, hold significant promise as an effective solution to the current antimicrobial resistance (AMR) crisis. Several AMPs have been identified and evaluated for their therapeutic application, with many already in the drug development pipeline. Their distinct properties, such as high target specificity, potency, and ability to bypass microbial resistance mechanisms, make AMPs a promising alternative to traditional antibiotics. Nonetheless, several challenges, such as high toxicity, lability to proteolytic degradation, low stability, poor pharmacokinetics, and high production costs, continue to hamper their clinical applicability. Therefore, recent research has focused on optimizing the properties of AMPs to improve their performance. By understanding the physicochemical properties of AMPs that correspond to their activity, such as amphipathicity, hydrophobicity, structural conformation, amino acid distribution, and composition, researchers can design AMPs with desired and improved performance. In this review, we highlight some of the key strategies used to optimize the performance of AMPs, including rational design and de novo synthesis. We also discuss the growing role of predictive computational tools, utilizing artificial intelligence and machine learning, in the design and synthesis of highly efficacious lead drug candidates.
Since the late 2010s, Artificial Intelligence (AI) including machine learning, boosted through deep learning, has boomed as a vital tool to leverage computer vision, natural language processing and speech recognition in revolutionizing zoological research. This review provides an overview of the primary tasks, core models, datasets, and applications of AI in zoological research, including animal classification, resource conservation, behavior, development, genetics and evolution, breeding and health, disease models, and paleontology. Additionally, we explore the challenges and future directions of integrating AI into this field. Based on numerous case studies, this review outlines various avenues for incorporating AI into zoological research and underscores its potential to enhance our understanding of the intricate relationships that exist within the animal kingdom. As we build a bridge between beast and byte realms, this review serves as a resource for envisioning novel AI applications in zoological research that have not yet been explored.
Alzheimer’s disease (AD) is an age-related progressive neurodegenerative disorder that leads to cognitive impairment and memory loss. Emerging evidence suggests that autophagy plays an important role in the pathogenesis of AD through the regulation of amyloid-beta (Aβ) and tau metabolism, and that autophagy dysfunction exacerbates amyloidosis and tau pathology. Therefore, targeting autophagy may be an effective approach for the treatment of AD. Animal models are considered useful tools for investigating the pathogenic mechanisms and therapeutic strategies of diseases. This review aims to summarize the pathological alterations in autophagy in representative AD animal models and to present recent studies on newly discovered autophagy-stimulating interventions in animal AD models. Finally, the opportunities, difficulties, and future directions of autophagy targeting in AD therapy are discussed.
Letter to the editor
Research highlight