Development of antibody-detection ELISA based on beta-bungarotoxin for evaluation of the neutralization potency of equine plasma against Bungarus multicinctus in Taiwan

Animal testing has been the primary approach to assess the neutralization potency of antivenom for decades. However, the necessity to sacrifice large numbers of experimental animals during this process has recently raised substantial welfare concerns. Furthermore, the laborious and expensive nature of animal testing highlights the critical need to develop alternative in vitro assays. Here, we developed an antibody-detection enzyme-linked immunosorbent assay (ELISA) technique as an alternative approach to evaluate the neutralization potency of hyperimmunized equine plasma against B. multicinctus, a medically important venomous snake in Taiwan. Firstly, five major protein components of B. multicinctus venom, specifically, α-BTX, β-BTX, γ-BTX, MTX, and NTL, were isolated. To rank their relative medical significance, a toxicity score system was utilized. Among the proteins tested, β-BTX presenting the highest score was regarded as the major toxic component. Subsequently, antibody-detection ELISA was established based on the five major proteins and used to evaluate 55 hyperimmunized equine plasma samples with known neutralization potency. ELISA based on β-BTX, the most lethal protein according to the toxicity score, exhibited the best sensitivity (75.6 %) and specificity (100 %) in discriminating between high-potency and low-potency plasma, supporting the hypothesis that highly toxic proteins offer better discriminatory power for potency evaluation. Additionally, a phospholipase A2 (PLA2) competition process was implemented to eliminate the antibodies targeting toxicologically irrelevant domains. This optimization greatly enhanced the performance of our assay, resulting in sensitivity of 97.6 % and specificity of 92.9 %. The newly developed antibody-detection ELISA presents a promising alternative to in vivo assays to determine the neutralization potency of antisera against B. multicinctus during the process of antivenom production.

Systematic review and meta-analysis on the efficacy of Indian polyvalent antivenom against the Indian snakes of clinical significance

Snakebite in India is a severe problem as it causes a mortality rate of 58,000 and a disability rate of 140,000 every year which is the highest among any other country. Antivenom is the primary therapy for snakebite, and its manufacturing techniques have essentially stayed unaltered for over a century. Indian polyvalent antivenom, a scientifically validated medicine for treating the toxic effects of snakebites, is available against the venom of the so-called Big Four snakes namely Spectacled cobra (Naja naja), Saw-scaled viper (Echis carinatus), Russell's viper (Daboia russelli) and the Common krait (Bungarus caeruleus), responsible for majority of the deaths in India. India hosts many other species of snakes, including cobras, kraits, saw-scaled vipers, sea snakes, and pit vipers, responsible for clinically severe envenomation. Neutralization strategy has been applied to access the efficacy of antivenoms, crucial for reducing snake bite deaths and disabilities. This review aims to conduct a systematic review and meta-analysis on the neutralization efficiency of the Polyvalent Antivenom (PAV) and focus on the factors that may contribute to the poor recognition of the antivenom towards the venom toxins. Reports focusing on the investigation of antivenom efficacy were searched and collected from several databases. Preclinical studies that reported the neutralization efficacy of the commercial antivenom against the medically important snakes of India were included. The articles were screened based on the inclusion criteria and 8 studies were shortlisted for meta-analysis. Pooled proportion was calculated for the antivenom efficacy reported by the studies and was found to be statistically significant with a 95% confidence interval. The heterogenicity in the venom toxicity and neutralization potency of the antivenom was evident in the overall estimate (proportion) and individual data. We provide comprehensive evidence on antivenom efficacy against medically important snakes from various parts of India which may aid in identifying the gaps in snake envenomation therapy and the need for novel potentially improved treatment of snakebites.

The applications of machine learning in HIV neutralizing antibodies research-A systematic review

Machine learning algorithms play an essential role in bioinformatics and allow exploring the vast and noisy biological data in unrivaled ways. This paper is a systematic review of the applications of machine learning in the study of HIV neutralizing antibodies. This significant and vast research domain can pave the way to novel treatments and to a vaccine. We selected the relevant papers by investigating the available literature from the Web of Science and PubMed databases in the last decade. The computational methods are applied in neutralization potency prediction, neutralization span prediction against multiple viral strains, antibody-virus binding sites detection, enhanced antibodies design, and the study of the antibody-induced immune response. These methods are viewed from multiple angles spanning data processing, model description, feature selection, evaluation, and sometimes paper comparisons. The algorithms are diverse and include supervised, unsupervised, and generative types. Both classical machine learning and modern deep learning were taken into account. The review ends with our ideas regarding future research directions and challenges.