Six host range variants of the xenotropic/polytropic gammaretroviruses define determinants for entry in the XPR1 cell surface receptor

<p>Abstract</p> <p>Background</p> <p>The evolutionary interactions between retroviruses and their receptors result in adaptive selection of restriction variants that can allow natural populations to evade retrovirus infection. The mouse xenotropic/polytropic (X/PMV) gammaretroviruses rely on the XPR1 cell surface receptor for entry into host cells, and polymorphic variants of this receptor have been identified in different rodent species.</p> <p>Results</p> <p>We screened a panel of X/PMVs for infectivity on rodent cells carrying 6 different XPR1 receptor variants. The X/PMVs included 5 well-characterized laboratory and wild mouse virus isolates as well as a novel cytopathic XMV-related virus, termed Cz524, isolated from an Eastern European wild mouse-derived strain, and XMRV, a xenotropic-like virus isolated from human prostate cancer. The 7 viruses define 6 distinct tropisms. Cz524 and another wild mouse isolate, CasE#1, have unique species tropisms. Among the PMVs, one Friend isolate is restricted by rat cells. Among the XMVs, two isolates, XMRV and AKR6, differ from other XMVs in their PMV-like restriction in hamster cells. We generated a set of <it>Xpr1 </it>mutants and chimeras, and identified critical amino acids in two extracellular loops (ECLs) that mediate entry of these different viruses, including 3 residues in ECL3 that are involved in PMV entry (E500, T507, and V508) and can also influence infectivity by AKR6 and Cz524.</p> <p>Conclusion</p> <p>We used a set of natural variants and mutants of <it>Xpr1 </it>to define 6 distinct host range variants among naturally occurring X/PMVs (2 XMV variants, 2 PMVs, 2 different wild mouse variants). We identified critical amino acids in XPR1 that mediate entry of these viruses. These gammaretroviruses and their XPR1 receptor are thus highly functionally polymorphic, a consequence of the evolutionary pressures that favor both host resistance and virus escape mutants. This variation accounts for multiple naturally occurring virus resistance phenotypes and perhaps contributes to the widespread distribution of these viruses in rodent and non-rodent species.</p

Comparative study on the gut microbiotas of four economically important Asian carp species

Gut microbiota of four economically important Asian carp species (silver carp, Hypophthalmichthys molitrix; bighead carp, Hypophthalmichthys nobilis; grass carp, Ctenopharyngodon idella; common carp, Cyprinus carpio) were compared using 16S rRNA gene pyrosequencing. Analysis of more than 590,000 quality-filtered sequences obtained from the foregut, midgut and hindgut of these four carp species revealed high microbial diversity among the samples. The foregut samples of grass carp exhibited more than 1,600 operational taxonomy units (OTUs) and the highest alpha-diversity index, followed by the silver carp foregut and midgut. Proteobacteria, Firmicutes, Bacteroidetes and Fusobacteria were the predominant phyla regardless of fish species or gut type. Pairwise (weighted) UniFrac distance-based permutational multivariate analysis of variance with fish species as a factor produced significant association (P &lt; 0.01). The gut microbiotas of all four carp species harbored saccharolytic or proteolytic microbes, likely in response to the differences in their feeding habits. In addition, extensive variations were also observed even within the same fish species. Our results indicate that the gut microbiotas of Asian carp depend on the exact species, even when the different species were cohabiting in the same environment. This study provides some new insights into developing commercial fish feeds and improving existing aquaculture strategies.</p

Necessary Sequencing Depth and Clustering Method to Obtain Relatively Stable Diversity Patterns in Studying Fish Gut Microbiota

The 16S rRNA gene is one of the most commonly used molecular markers for estimating bacterial diversity during the past decades. However, there is no consistency about the sequencing depth (from thousand to millions of sequences per sample), and the clustering methods used to generate OTUs may also be different among studies. These inconsistent premises make effective comparisons among studies difficult or unreliable. This study aims to examine the necessary sequencing depth and clustering method that would be needed to ensure a stable diversity patterns for studying fish gut microbiota. A total number of 42 samples dataset of Siniperca chuatsi (carnivorous fish) gut microbiota were used to test how the sequencing depth and clustering may affect the alpha and beta diversity patterns of fish intestinal microbiota. Interestingly, we found that the sequencing depth (resampling 1000-11,000 per sample) and the clustering methods (UPARSE and UCLUST) did not bias the estimates of the diversity patterns during the fish development from larva to adult. Although we should acknowledge that a suitable sequencing depth may differ case by case, our finding indicates that a shallow sequencing such as 1000 sequences per sample may be also enough to reflect the general diversity patterns of fish gut microbiota. However, we have shown in the present study that strict pre-processing of the original sequences is required to ensure reliable results. This study provides evidences to help making a strong scientific choice of the sequencing depth and clustering method for future studies on fish gut microbiota patterns, but at the same time reducing as much as possible the costs related to the analysis.</p

Spatiotemporal heterogeneity of plankton communities in Lake Donghu, China, as revealed by PCR-denaturing gradient gel electrophoresis and its relation to biotic and abiotic factors

The 16S and 18S rRNA genes of planktonic organisms derived from five stations with nutrient gradients in Lake Donghu, China, were studied by PCR-denaturing gradient gel electrophoresis (DGGE) fingerprinting, and the relationships between the genetic diversity of the plankton community and biotic/abiotic factors are discussed. The concentrations of total nitrogen (TN), total phosphorus (TP), NH4-N and As were found to be significantly related (P < 0.05) to morphological composition of the plankton community. Both chemical and morphological analyses suggested that temporal heterogeneity was comparatively higher than spatial heterogeneity in Lake Donghu. Although the morphological composition was not identical to the DGGE fingerprints in characterizing habitat similarity, the two strongest eutrophic stations (I and II) were always initially grouped into one cluster. Canonical correspondence analysis suggested that the factors strongly correlated with the first two ordination axes were seasonally different. The concentrations of TN and TP and the densities of rotifers and crustaceans were generally the main factors related to the DGGE patterns of the plankton communities. The study suggested that genetic diversity as depicted by metagenomic techniques (such as PCR-DGGE fingerprinting) is a promising tool for ecological study of plankton communities and that such techniques are likely to play an increasingly important role in assessing the environmental conditions of aquatic habitats.The 16S and 18S rRNA genes of planktonic organisms derived from five stations with nutrient gradients in Lake Donghu, China, were studied by PCR-denaturing gradient gel electrophoresis (DGGE) fingerprinting, and the relationships between the genetic diversity of the plankton community and biotic/abiotic factors are discussed. The concentrations of total nitrogen (TN), total phosphorus (TP), NH4-N and As were found to be significantly related (P < 0.05) to morphological composition of the plankton community. Both chemical and morphological analyses suggested that temporal heterogeneity was comparatively higher than spatial heterogeneity in Lake Donghu. Although the morphological composition was not identical to the DGGE fingerprints in characterizing habitat similarity, the two strongest eutrophic stations (I and II) were always initially grouped into one cluster. Canonical correspondence analysis suggested that the factors strongly correlated with the first two ordination axes were seasonally different. The concentrations of TN and TP and the densities of rotifers and crustaceans were generally the main factors related to the DGGE patterns of the plankton communities. The study suggested that genetic diversity as depicted by metagenomic techniques (such as PCR-DGGE fingerprinting) is a promising tool for ecological study of plankton communities and that such techniques are likely to play an increasingly important role in assessing the environmental conditions of aquatic habitats

Fine-tuning Large Language Model (LLM) Artificial Intelligence Chatbots in Ophthalmology and LLM-based evaluation using GPT-4

Purpose: To assess the alignment of GPT-4-based evaluation to human clinician experts, for the evaluation of responses to ophthalmology-related patient queries generated by fine-tuned LLM chatbots. Methods: 400 ophthalmology questions and paired answers were created by ophthalmologists to represent commonly asked patient questions, divided into fine-tuning (368; 92%), and testing (40; 8%). We find-tuned 5 different LLMs, including LLAMA2-7b, LLAMA2-7b-Chat, LLAMA2-13b, and LLAMA2-13b-Chat. For the testing dataset, additional 8 glaucoma QnA pairs were included. 200 responses to the testing dataset were generated by 5 fine-tuned LLMs for evaluation. A customized clinical evaluation rubric was used to guide GPT-4 evaluation, grounded on clinical accuracy, relevance, patient safety, and ease of understanding. GPT-4 evaluation was then compared against ranking by 5 clinicians for clinical alignment. Results: Among all fine-tuned LLMs, GPT-3.5 scored the highest (87.1%), followed by LLAMA2-13b (80.9%), LLAMA2-13b-chat (75.5%), LLAMA2-7b-Chat (70%) and LLAMA2-7b (68.8%) based on the GPT-4 evaluation. GPT-4 evaluation demonstrated significant agreement with human clinician rankings, with Spearman and Kendall Tau correlation coefficients of 0.90 and 0.80 respectively; while correlation based on Cohen Kappa was more modest at 0.50. Notably, qualitative analysis and the glaucoma sub-analysis revealed clinical inaccuracies in the LLM-generated responses, which were appropriately identified by the GPT-4 evaluation. Conclusion: The notable clinical alignment of GPT-4 evaluation highlighted its potential to streamline the clinical evaluation of LLM chatbot responses to healthcare-related queries. By complementing the existing clinician-dependent manual grading, this efficient and automated evaluation could assist the validation of future developments in LLM applications for healthcare.Comment: 13 Pages, 1 Figure, 8 Table