Antibiofilm activity of Morganella morganii JB8F and Pseudomonas fluorescens JB3B compound to control single and multi-species of aquaculture pathogens.

BACKGROUND: Indonesia is a country that uses half or more aquatic foods as protein intake. The increased production in aquaculture industries might cause several problems, such as bacterial disease resulting in mass mortality and economic losses. Antibiotics are no longer effective because aquaculture pathogens can form biofilm. Biofilm is a microbial community that aggregates and firmly attaches to living or non-living surfaces. Biofilm formation can be caused by environmental stress, the presence of antibiotics, and limited nutrients. Therefore, it is important to explore antibiofilm to inhibit biofilm formation and/or eradicate mature biofilm. Phyllosphere bacteria can produce bioactive compounds for antimicrobial, antibiofilm, and anti-quorum sensing. Three aquaculture pathogens were used in this study, such as Aeromonas hydrophila, Streptococcus agalactiae, and Vibrio harveyi. RESULTS: Pseudomonas fluorescens JB3B and Morganella morganii JB8F extracts could disrupt single and multi-species biofilms. Both extracts could inhibit single biofilm formation from one to seven days of incubation time. We confirmed the destruction activity on multi-species biofilm using light microscope and scanning electron microscope. Using GC-MS analysis, indole was the most active fraction of the P. fluorescens JB3B extracts and octacosane from the M. morganii JB8F extract. We also conducted a toxicity test using brine shrimp lethality assay on P. fluorescens JB3B and M. morganii JB8F extracts. P. fluorescens JB3B, M. morganii JB8F, and a mixture of both extracts were confirmed non-toxic according to the LC50 value of the brine shrimp lethality test. CONCLUSIONS: P. fluorescens JB3B and M. morganii JB8F phyllosphere extracts had antibiofilm activity to inhibit single biofilm and disrupt single and multi-species biofilm of aquaculture pathogens. Both extracts could inhibit single species biofilm until seven days of incubation. Bioactive compounds that might contribute to antibiofilm properties were found in both extracts, such as indole and phenol. P. fluorescens JB3B, M. morganii JB8F extracts, and mixture of both extracts were non-toxic against Artemia salina.

Microbial Ecology of Nitrate-, Selenate-, Selenite-, and Sulfate-Reducing Bacteria in a H2-Driven Bioprocess.

A hydrogen (H2)-based membrane biofilm reactor (H2-MBfR) can reduce electron acceptors nitrate (NO3-), selenate (SeO42-), selenite (HSeO3-), and sulfate (SO42-), which are in wastewaters from coal mining and combustion. This work presents a model to describe a H2-driven microbial community comprised of hydrogenotrophic and heterotrophic bacteria that respire NO3-, SeO42-, HSeO3-, and SO42-. The model provides mechanistic insights into the interactions between autotrophic and heterotrophic bacteria in a microbial community that is founded on H2-based autotrophy. Simulations were carried out for a range of relevant solids retention times (0.1 to 20 days) and with adequate H2-delivery capacity to reduce all electron acceptors. Bacterial activity began at an ∼0.6-day SRT, when hydrogenotrophic denitrifiers began to accumulate. Selenate-reducing and selenite-reducing hydrogenotrophs became established next, at SRTs of ∼1.2 and 2 days, respectively. Full nitrate, selenate, and selenite reductions were complete by an SRT of ∼5 days. Sulfate reduction began at an SRT of ∼10 days and was complete by ∼15 days. The desired goal of reducing nitrate, selenate, and selenite, but not sulfate, was achievable within an SRT window of 5 to 10 days. Autotrophic hydrogenotrophs dominated the active biomass, but non-active solids were a major portion of the solids, especially for an SRT ≥ 5 days.

Advances and challenges in ecological connectivity science.

Maintaining and restoring ecological connectivity will be key in helping to prevent and reverse the loss of biodiversity. Fortunately, a growing body of research conducted over the last few decades has advanced our understanding of connectivity science, which will help inform evidence-based connectivity conservation actions. Increases in data availability and computing capacity have helped to dramatically increase our ability to model functional connectivity using more sophisticated models. Keeping track of these advances can be difficult, even for connectivity scientists and practitioners. In this article, we highlight some key advances from the past decade and outline many of the remaining challenges. We describe the efforts to increase the biological realism of connectivity models by, for example, isolating movement behaviors, population parameters, directional movements, and the effects of climate change. We also discuss considerations of when to model connectivity for focal or multiple species. Finally, we reflect on how to account for uncertainty and increase the transparency and reproducibility of connectivity research and discuss situations where decisions may require forgoing sophistication for more simple approaches.

Moving Toward Evidence-Based Care: Measuring Preferences in Zoo-Housed Aquatic Turtles Using 24-h Remote Monitoring.

Providing evidence-based care to animals is a common goal in zoos and aquariums. However, there are many understudied species with a lack of information available, which may result in suboptimal care for individuals of these species. Using preference tests to ask individual animals what they want can be an effective means to enhance their care, and subsequently, their welfare. Using 24-h remote monitoring, we assessed substrate, enclosure feature, and lighting preferences of five aquatic turtles (two wood turtles, one Blanding's turtle, and two spotted turtles) that share an indoor enclosure at Lincoln Park Zoo. In addition, we compared enclosure feature and lighting preferences between winter and summer to determine whether the turtles had changing seasonal preferences despite being housed indoors. We found that the wood turtles and Blanding's turtle had substrate preferences, whereas the spotted turtles did not. In addition, we found that the turtles' enclosure feature preferences were consistent between winter and summer, but the amount of time spent on land, logs, and in water varied by individual. Finally, we found that the turtles utilized areas with ambient lighting more than areas with a heat lamp or UV lamp; this was consistent between winter and summer. The turtle preferences observed in this study can contribute to the development of care strategies that support their welfare and, in turn, may inspire similar preference studies at other institutions as we collectively advance toward providing animals of all taxonomic groups with evidence-based care.

Reuterin Enhances the Efficacy of Peracetic Acid Against Multi-species Dairy Biofilm.

Biofilms may contain pathogenic and spoilage bacteria and can become a recurring problem in the dairy sector, with a negative impact on product quality and consumer health. Peracetic acid (PAA) is one of the disinfectants most frequently used to control biofilm formation and persistence. Though effective, it cannot be used at high concentrations due to its corrosive effect on certain materials and because of toxicity concerns. The aim of this study was to test the possibility of PAA remaining bactericidal at lower concentrations by using it in conjunction with reuterin (3-hydroxypropionaldehyde). We evaluated the efficacy of PAA in pure form or as BioDestroy®, a PAA-based commercial disinfectant, on three-species biofilms formed by dairy-derived bacteria, namely Pseudomonas azotoformans PFlA1, Serratia liquefaciens Sl-LJJ01, and Bacillus licheniformis Bl-LJJ01. Minimum inhibitory concentrations of the three agents were determined for each bacterial species and the fractional inhibitory concentrations were then calculated using the checkerboard assay. The minimal biofilm eradication concentration (MBEC) of each antibacterial combination was then calculated against mixed-species biofilm. PAA, BioDestroy®, and reuterin showed antibiofilm activity against all bacteria within the mixed biofilm at respectively 760 ppm, 450 ppm, and 95.6 mM. The MBEC was lowered significantly to 456 ppm, 337.5 ppm, and 71.7 mM, when exposed to reuterin for 16 h followed by contact with disinfectant. Combining reuterin with chemical disinfection shows promise in controlling biofilm on food contact surfaces, especially for harsh or extended treatments. Furthermore, systems with reuterin encapsulation and nanotechnologies could be developed for sustainable antimicrobial efficacy without manufacturing disruptions.

Decoding Seafood: Multi-Marker Metabarcoding for Authenticating Processed Seafood.

Given the recognized nutritional value of fish and shifting consumer lifestyles, processed seafood has become increasingly prevalent, comprising a significant portion of global food production. Although current European Union labeling regulations do not require species declaration for these products, food business operators often voluntarily provide this information on ingredient lists. Next Generation Sequencing (NGS) approaches are currently the most effective methods for verifying the accuracy of species declarations on processed seafood labels. This study examined the species composition of 20 processed seafood products, each labeled as containing a single species, using two DNA metabarcoding markers targeting the mitochondrial cytochrome c oxidase I (COI) and 16S rRNA genes. The combined use of these markers revealed that the majority of the products contained multiple species. Furthermore, two products were found to be mislabeled, as the declared species were not detected. These findings underscore that NGS is a robust technique that could be adopted to support routine food industry activities and official control programs, thereby enhancing the 'From Boat to Plate' strategy and combating fraudulent practices in the complex fisheries supply chain.

Whole genome phylogenomics helps to resolve the phylogenetic position of the Zygothrica genus group (Diptera, Drosophilidae) and the causes of previous incongruences.

Incomplete Lineage Sorting (ILS) and introgression are among the two main factors causing incongruence between gene and species trees. Advances in phylogenomic studies have allowed us to overcome most of these issues, providing reliable phylogenetic hypotheses while revealing the underlying evolutionary scenario. Across the last century, many incongruent phylogenetic reconstructions were recovered for Drosophilidae, employing a limited sampling of genetic markers or species. In these studies, the monophyly and the phylogenetic positioning of the Zygothrica genus group stood out as one of the most controversial questions. Thus, here, we addressed these issues using a phylogenomic approach, while accessing the influence of ILS and introgressions on the diversification of these species and addressing the spatio-temporal scenario associated with their evolution. For this task, the genomes of nine specimens from six Neotropical species belonging to the Zygothrica genus group were sequenced and evaluated in a phylogenetic framework encompassing other 39 species of Drosophilidae. Nucleotide and amino acid sequences recovered for a set of 2,534 single-copy genes by BUSCO were employed to reconstruct maximum likelihood (ML) concatenated and multi-species coalescent (MSC) trees. Likelihood mapping, quartet sampling, and reticulation tests were employed to infer the level and causes of incongruence. Lastly, a penalized-likelihood molecular clock strategy with fossil calibrations was performed to infer divergence times. Taken together, our results recovered the subdivision of Drosophila into six different lineages, one of which clusters species of the Zygothrica genus group (except for H. duncani). The divergence of this lineage was dated to Oligocene âˆ¼ 31 Mya and seems to have occurred in the same timeframe as other key diversification within Drosophila. According to the concatenated and MSC strategies, this lineage is sister to the clade joining Drosophila (Siphlodora) with the Hawaiian Drosophila and Scaptomyza. Likelihood mapping, quartet sampling, reticulation reconstructions as well as introgression tests revealed that this lineage was the target of several hybridization events involving the ancestors of different Drosophila lineages. Thus, our results generally show introgression as a major source of previous incongruence. Nevertheless, the similar diversification times recovered for several of the Neotropical Drosophila lineages also support the scenario of multiple and simultaneous diversifications taking place at the base of Drosophilidae phylogeny, at least in the Neotropics.

Formation of filamentous fungal biofilms in water and the transformation of resistance to chlor(am)ine disinfection.

Biofilms are composed of complex multi-species in nature, potentially threatening drinking water safety. In this work, the formation of single- and multi-species fungal biofilms formed by Aspergillus niger (A. niger) and Aspergillus flavus (A. flavus), and the inactivation of mature biofilms using chlor(am)ine were firstly investigated. Results revealed that the antagonistic interaction occurred between A. niger and A. flavus. Chloramination at 20 mg/L for 30 min achieved 74.74 % and 76.04 % inactivation of A. flavus and multi-species biofilm, which were 1.69- and 1.84-fold higher than that of chlorine at the same condition. However, no significant difference was observed in the inactivation of A. niger biofilm between chlorine and monochloramine disinfection due to the lower amount of extracellular polymeric substance produced by it (p > 0.05). The inactivation of biofilm by monochloramine fitted the Weibull model well. According to the Weibull model, the monochloramine resistance of biofilm were as follows: A. flavus > multi-species > A. niger biofilm. Besides, an increase in reactive oxygen levels, damage of cell membrane, and leakage of intracellular substances in biofilms were observed after chlor(am)ination. More intracellular polysaccharides and proteins were leaked in chloramination inactivation (p < 0.05). This study provides important implications for controlling fungal biofilm.

Accounting for imperfect detection when estimating species-area relationships and beta-diversity.

Ecologists have historically quantified fundamental biodiversity patterns, including species-area relationships (SARs) and beta diversity, using observed species counts. However, imperfect detection may often bias derived community metrics and subsequent community models. Although several statistical methods claim to correct for imperfect detection, their performance in species-area and ß-diversity research remains unproven. We examine inaccuracies in the estimation of SARs and ß-diversity parameters that emerge from imperfect detection, and whether such errors can be mitigated using a non-parametric diversity estimator (iNEXT.3D) and Multi-Species Occupancy Models (MSOMs). We simulated 28,350 sampling regimes of 2835 fragmented communities, varying the mean and standard deviation of species detection probabilities, and the number of sampling repetitions. We then quantified the bias, accuracy, and precision of derived estimates of model coefficients for SARs and the effects of patch area on ß-diversity (pairwise Sørensen similarity). Imperfect detection biased estimates of all evaluated parameters, particularly when mean detection probabilities were low, and there were few sampling repetitions. Observed counts consistently underestimated species richness and SAR z-values, and overestimated SAR c-values; iNEXT.3D and MSOMs only partially resolved these biases. iNEXT.3D provided the best estimates of SAR z-values, although MSOM estimates were generally comparable. All three methods accurately estimated pairwise Sørensen similarity in most circumstances, but only MSOMs provided unbiased estimates of the coefficients of models examining covariate effects on ß-diversity. Even when using iNEXT.3D or MSOMs, imperfect detection consistently caused biases in SAR coefficient estimates, calling into question the robustness of previous SAR studies. Furthermore, the inability of observed counts and iNEXT.3D to estimate ß-diversity model coefficients resulted from a systematic, area-related bias in Sørensen similarity estimates. Importantly, MSOMs corrected for these biases in ß-diversity assessments, even in suboptimal scenarios. Nonetheless, as estimator performance consistently improved with increasing sampling repetitions, the importance of appropriate sampling effort cannot be understated.

Species richness and evenness of European bird communities show differentiated responses to measures of productivity.

Understanding patterns of species diversity is crucial for ecological research and conservation, and this understanding may be improved by studying patterns in the two components of species diversity, species richness and evenness of abundance of species. Variation in species richness and evenness has previously been linked to variation in total abundance of communities as well as productivity gradients. Exploring both components of species diversity is essential because these components could be unrelated or driven by different mechanisms. The aim of this study was to investigate the relationship between species richness and evenness in European bird communities along an extensive latitudinal gradient. We examined their relationships with latitude and Net Primary Productivity, which determines energy and matter availability for heterotrophs, as well as their responses to territory densities (i.e. the number of territories per area) and community biomass (i.e. the bird biomass per area). We applied a multivariate Poisson log-normal distribution to unique long-term, high-quality time-series data, allowing us to estimate species richness of the community as well as the variance of this distribution, which acts as an inverse measure of evenness. Evenness in the distribution of abundance of species in the community was independent of species richness. Species richness increased with increasing community biomass, as well as with increasing density. Since both measures of abundance were explained by NPP, species richness was partially explained by energy-diversity theory (i.e. the more energy, the more species sustained by the ecosystem). However, species richness did not increase linearly with NPP but rather showed a unimodal relationship. Evenness was not explained either by productivity nor by any of the aspects of community abundance. This study highlights the importance of considering both richness and evenness to gain a better understanding of variation in species diversity. We encourage the study of both components of species diversity in future studies, as well as use of simulation studies to verify observed patterns between richness and evenness.

Ecological restoration at pilot-scale employing site-specific rationales for small-patch degraded mangroves in Indian Sundarbans.

To date, degraded mangrove ecosystem restoration accomplished worldwide primarily aligns towards rehabilitation with monotypic plantations, while ecological restoration principles are rarely followed in these interventions. However, researchers admit that most of these initiatives' success rate is not appreciable often. An integrative framework of ecological restoration for degraded mangroves where site-specific observations could be scientifically rationalized, with co-located reference pristine mangroves as the target ecosystem to achieve is currently distinctively lacking. Through this experimental scale study, we studied the suitability of site-specific strategies to ecologically restore degraded mangrove patches vis-à-vis the conventional mono-species plantations in a highly vulnerable mangrove ecosystem in Indian Sundarbans. This comprehensive restoration framework was trialed in small discrete degraded mangrove patches spanning ~ 65 ha. Site-specific key restoration components applied are statistically validated through RDA analyses and Bayesian t-tests. 25 quantifiable metrics evaluate the restoration success of a ~ 3 ha degraded mangrove patch with Ridgeline distribution, Kolmogorov-Smirnov (K-S) tests, and Mahalanobis Distance (D2) measure to prove the site's near-equivalence to pristine reference in multiple ecosystem attributes. This restoration intervention irrevocably establishes the greater potential of this framework in the recovery of ecosystem functions and self-sustenance compared to that of predominant monoculture practices for vulnerable mangroves.

Label-Free Quantitative Proteomics of Oral Microbial Communities.

The oral cavity is a habitat for different microorganisms, of which bacteria are best described. Studying different bacterial taxa and their proteins is crucial to understanding their interactions with the host and other microbes. Also, for bacteria with virulence potential, identifying novel antigenic proteins is essential to finding candidates for the development of vaccines.Here, a workflow for gel-free and label-free protein analysis of oral bacterial species grown in vitro as a biofilm and a planktonic culture is described. Details on cultivation, protein extraction and digestion, peptide cleanup, LC-MS/MS run parameters, and subsequent bioinformatics analysis are included. Challenging steps in the workflow, such as growing different types of bacteria and selecting a suitable protein database, are also discussed. This protocol provides a valuable guide for metaproteomic experiments using multi-species models of oral bacteria.

Dairy farming technologies and the agency of cows.

Studies on animal cognition, emotion, language, culture, and politics have shown that non-human animals are agents who engage in self-willed actions and have an interest in shaping their own lives. In today's world, however, animals' lives are affected significantly by circumstances that humans have created, including animal farming systems. The current paper explores how the agency of cows relates to technology by reporting on fieldwork performed in the Dutch dairy sector. Multi-species ethnography was used as a flexible methodology that allowed readjusting questions and methods as our research developed. In the first research phase, observations and informal talks were held on six farms which had been recruited on the basis of convenience sampling and which were each visited for one full day. In the second research phase, five more farms were selected for 1-day visits through theoretical and snowball sampling, and one farm was visited repeatedly for in-depth observations. The observational strategies used included following individual actors (farmers, cows or technologies) and documenting their interactions with other actors; participating in daily routines such as feeding cows roughage and scraping manure; witnessing cows' responses to non-routine events such as the introduction of new technologies or new cows; and sometimes waiting for notable occurrences by just 'hanging out' with cows. Observations and informal talks were in this research phase complemented by a small number of interviews with farmers, cow shed designers, and technology developers. Our main conclusion is that the agency of dairy cows is presupposed and mediated by dairy farming technologies. Dairy farming technologies presuppose cow in the 'scripts' and 'programs of action' which they enforce: they require cows to act in specific ways, anticipate some ways in which cows could disrupt technological routines, and (successfully or unsuccessfully) attempt to ensure cows' cooperation by appealing to their wants and desires and their ability to learn. Dairy farming technologies thus assign to cows not only the ability to perform 'metabolic labour' but also the capacity to act purposively and learning abilities. Technologies mediate cow agency by (co-)shaping how cows express agency in relation to other entities, including other cows, humans, other non-human animals, material entities including technologies, and the world at large. That technologies can be relevant for animal agency in various ways raises the question of how technologies can be designed for agency - although the concept of animal agency also challenges us to reconsider animal agriculture more fundamentally.

Specific cultivation-independent enumeration of viable cells in probiotic products using a combination of fluorescence in situ hybridization and flow cytometry.

This study introduces an optimized integration of flow cytometry and fluorescence in situ hybridization (Flow-FISH) as an approach for the specific enumeration of gram-positive bacteria in probiotic products, overcoming the limitations of conventional methods. The enhanced Flow-FISH technique synergizes the rapid and automated capabilities of flow cytometry with the high specificity of FISH, facilitating the differentiation of viable cells at the species level within probiotic blends. By analyzing lyophilized samples of Lacticaseibacillus rhamnosus, Lactiplantibacillus plantarum, and Bifidobacterium animalis subsp. lactis, and a commercial product, the study highlights the optimized Flow-FISH protocol's advantages, including reduced hybridization times to 1.5 h and elimination of centrifugation steps. Comparative evaluations with the widely accepted enumeration methods plate count and Live/Dead (L/D) staining were conducted. The study revealed that Flow-FISH produces higher viable cell counts than plate count, thereby challenging the traditional "gold standard" by highlighting its predisposition to underestimate actual viable cell numbers. Against L/D staining, Flow-FISH achieved comparable results, which, despite the different foundational premises of each technique, confirms the accuracy and reliability of our method. In conclusion, the optimized Flow-FISH protocol represents a significant leap forward in probiotic research and quality control. This method provides a rapid, robust, and highly specific alternative for the enumeration of probiotic bacteria, surpassing traditional methodologies. Its ability to enable a more detailed and reliable analysis of probiotic products paves the way for precise quality control and research insights, underscoring its potential to improve the field significantly.

No differences were observed in the prevention of necrotizing enterocolitis and late-onset sepsis among preterm infants who received either single-species or multi-species probiotics.

BACKGROUND: Probiotic prophylaxis has been suggested to reduce the incidence of necrotizing enterocolitis (NEC) and late-onset sepsis (LOS) in very preterm newborns. However, choosing the optimal probiotic is difficult due to variations in strain-specific effects and interactions facilitated by the use of combination species. AIMS: To compare clinical outcomes of very preterm infants receiving multi or single-species probiotics. STUDY DESIGN: Retrospective, single-center, cohort study. SUBJECTS: Very preterm infants (<32 weeks' gestation) born between 2019 and 2022 at a tertiary perinatal center received either a multi-species (Lactobacillus rhamnosus 45 %, Lactobacillus casei 15 %, Lactobacillus acidophilus 15 %, Bifidobacterium infantis 15 %, Bifidobacterium bifidum 10 %; n = 228) or a single-species (Bifidobacterium breve BR03 and B632; n = 227) probiotic formulation. MAIN OUTCOME MEASURES: NEC, LOS, and mortality. RESULTS: The overall incidence of NEC and LOS was 3.1 % and 13.8 %, respectively. There were no differences between the multi-species and single-species probiotic groups in the rate of NEC (3.5 % vs 2.6 %; p = 0.787), LOS (15.4 % vs 12.3 %; p = 0.416), mortality (0.9 % vs 1.8 %; p = 0.449), or composite outcome (NEC, LOS and/or death; 16.7 % vs 12.8 %; p = 0.290). CONCLUSION: The clinical outcomes of very preterm newborns receiving multi vs. single-species probiotic formulations were similar in our study. In view of the sample size and low baseline rate of NEC in our unit, further trials are warranted to investigate the effects of specific probiotics for prevention of serious neonatal morbidities.

Difference in formation of a dental multi-species biofilm according to substratum direction.

OBJECTIVES: The aim of this study was to investigate the difference in dental biofilm formation according to substratum direction, using an artificial biofilm model. METHODS: A three-species biofilm, consisting of Streptococcus mutans, Streptococcus oralis, and Actinomyces naeslundii, was formed on saliva-coated hydroxyapatite (sHA) discs oriented in three directions: downward (the discs placed in the direction of gravity), vertical (the discs placed parallel to the direction of gravity), and upward (the discs placed in opposite direction of gravity). The biofilms at 22 h and 46 h of age were analyzed using microbiological and biochemical methods, fluorescence-based assays, and scanning electron microscopy to investigate difference in bacterial adhesion, early and mature biofilm formation. RESULTS: The biofilms formed in the upward direction displayed the most complex structure, with the highest number and biovolume of bacteria, as well as the lowest pH conditions at both time points. The vertical and downward directions, however, had only scattered and small bacterial colonies. In the 22-h-old biofilms, the proportion of S. oralis was similar to, or slightly higher than, that of S. mutans in all directions of substratum surfaces. However, in the 46-h-old biofilms, S. mutans became the dominant bacteria in all directions, especially in the vertical and upward directions. CONCLUSIONS: The direction of the substratum surface could impact the proportion of bacteria and cariogenic properties of the multi-species biofilm. Biofilms in an upward direction may exhibit a higher cariogenic potential, followed by those in the vertical and downward directions, which could be related to gravity.

DeepOCR: A multi-species deep-learning framework for accurate identification of open chromatin regions in livestock.

A wealth of experimental evidence has suggested that open chromatin regions (OCRs) are involved in many critical biological activities, such as DNA replication, enhancer activity, and gene transcription. Accurately identifying OCRs in livestock species can provide critical insights into the distribution and characteristics of OCRs for disease treatment in livestock, thereby improving animal welfare. However, most current machine-learning methods for OCR prediction were originally designed for a limited number of model organisms, such as humans and some model organisms, and thus their performance on non-model organisms, specifically livestock, is often unsatisfactory. To bridge this gap, we propose DeepOCR, a lightweight depth-separable residual network model for predicting OCRs in livestock, including chicken, cattle, and sheep. DeepOCR integrates a single convolution layer and two improved residue structure blocks to extract and learn important features from the input DNA sequences. A fully connected layer was also employed to further process the extracted features and improve the robustness of the entire network. Our benchmarking experiments demonstrated superior prediction performance of DeepOCR compared to state-of-the-art approaches on testing datasets of the three species. The source code of DeepOCR is freely available for academic purposes at https://github.com/jasonzhao371/DeepOCR/. We anticipate DeepOCR servers as a practical and reliable computational tool for OCR-related studies in livestock species.

TransAC4C-a novel interpretable architecture for multi-species identification of N4-acetylcytidine sites in RNA with single-base resolution.

N4-acetylcytidine (ac4C) is a modification found in ribonucleic acid (RNA) related to diseases. Expensive and labor-intensive methods hindered the exploration of ac4C mechanisms and the development of specific anti-ac4C drugs. Therefore, an advanced prediction model for ac4C in RNA is urgently needed. Despite the construction of various prediction models, several limitations exist: (1) insufficient resolution at base level for ac4C sites; (2) lack of information on species other than Homo sapiens; (3) lack of information on RNA other than mRNA; and (4) lack of interpretation for each prediction. In light of these limitations, we have reconstructed the previous benchmark dataset and introduced a new dataset including balanced RNA sequences from multiple species and RNA types, while also providing base-level resolution for ac4C sites. Additionally, we have proposed a novel transformer-based architecture and pipeline for predicting ac4C sites, allowing for highly accurate predictions, visually interpretable results and no restrictions on the length of input RNA sequences. Statistically, our work has improved the accuracy of predicting specific ac4C sites in multiple species from less than 40% to around 85%, achieving a high AUC > 0.9. These results significantly surpass the performance of all existing models.

Study on phosphonylation and modification characteristics of organophosphorus nerve agents on multi-species and multi-source albumins.

Protein adducts are vital targets for exploring organophosphorus nerve agents (OPNAs) exposure and identification, that can be used to characterize the chemical burden and initiate chemical safety measures. However, the use of protein adducts as biomarkers of OPNA exposure has developed slowly. To further promote the development of biomarkers in chemical forensics, it is crucial to expand the range of modified peptides and active sites, and describe the characteristics of OPNA adducts at specific reaction sites. This study utilized multi-species and multi-source albumins as the protein targets. We identified 56 peptides in albumins from various species (including human, horse, rat and pig), that were modified by at least two OPNAs. Diverse modification characteristics were observed in response to certain agents: including (1) multiple sites on the same peptide modified by one or more agents, (2) different reactivities at the same site in homologous albumins, and (3) different preferences at the same active sites associated with differences in the biological matrix during exposure. Our studies provided an empirical reference with rationalized underpinnings supported by estimated conformation energetics through molecular modeling. We employed different peptide markers for detection of protein adducts, as (one would do) in forensic screening for identification and quantification of chemical damage. Three characteristic peptides were screened and analyzed in human albumin, including Y287ICENQDSISSK, K438VPQVS443TPTLVEVSR, and Y162LY164EIAR. Stable fragment ions with neutral loss were found from their tandem MS/MS spectra, which were used as characteristic ions for identification and extraction of modified peptides in enzymatic digestion mixtures. Coupling these observations with computer simulations, we found that the structural stability of albumin and albumin-adduct complexes (as well as the effective force that promotes stability of different adducts) changes in the interval before and after adduct formation. In pig albumin, five active peptides existed stably in vivo and in vitro. Most of them can be detected within 30 min after OPNA exposure, and the detection window can persist about half a month. These early findings provided the foundation and rationale for utilizing pig albumin as a sampling target for rapid analysis in future forensic work.

nBEST: Deep-learning-based non-human primates Brain Extraction and Segmentation Toolbox across ages, sites and species.

Accurate processing and analysis of non-human primate (NHP) brain magnetic resonance imaging (MRI) serves an indispensable role in understanding brain evolution, development, aging, and diseases. Despite the accumulation of diverse NHP brain MRI datasets at various developmental stages and from various imaging sites/scanners, existing computational tools designed for human MRI typically perform poor on NHP data, due to huge differences in brain sizes, morphologies, and imaging appearances across species, sites, and ages, highlighting the imperative for NHP-specialized MRI processing tools. To address this issue, in this paper, we present a robust, generic, and fully automated computational pipeline, called non-human primates Brain Extraction and Segmentation Toolbox (nBEST), whose main functionality includes brain extraction, non-cerebrum removal, and tissue segmentation. Building on cutting-edge deep learning techniques by employing lifelong learning to flexibly integrate data from diverse NHP populations and innovatively constructing 3D U-NeXt architecture, nBEST can well handle structural NHP brain MR images from multi-species, multi-site, and multi-developmental-stage (from neonates to the elderly). We extensively validated nBEST based on, to our knowledge, the largest assemblage dataset in NHP brain studies, encompassing 1,469 scans with 11 species (e.g., rhesus macaques, cynomolgus macaques, chimpanzees, marmosets, squirrel monkeys, etc.) from 23 independent datasets. Compared to alternative tools, nBEST outperforms in precision, applicability, robustness, comprehensiveness, and generalizability, greatly benefiting downstream longitudinal, cross-sectional, and cross-species quantitative analyses. We have made nBEST an open-source toolbox (https://github.com/TaoZhong11/nBEST) and we are committed to its continual refinement through lifelong learning with incoming data to greatly contribute to the research field.