BACTIBASE: a new web-accessible database for bacteriocin characterization

<p>Abstract</p> <p>Background</p> <p>Bacteriocins are very diverse group of antimicrobial peptides produced by a wide range of bacteria and known for their inhibitory activity against various human and animal pathogens. Although many bacteriocins are now well characterized, much information is still missing or is unavailable to potential users. The assembly of such information in one central resource such as a database would therefore be of great benefit to the exploitation of these bioactive molecules in the present context of increasing antibiotic resistance and natural bio-preservation need.</p> <p>Description</p> <p>In the present paper, we present the development of a new and original database BACTIBASE that contains calculated or predicted physicochemical properties of 123 bacteriocins produced by both Gram-positive and Gram-negative bacteria. The information in this database is very easy to extract and allows rapid prediction of relationships structure/function and target organisms of these peptides and therefore better exploitation of their biological activity in both the medical and food sectors.</p> <p>Conclusion</p> <p>The BACTIBASE database is freely available at <url>http://bactibase.pfba-lab.org</url>, web-based platform enabling easy retrieval, via various filters, of sets of bacteriocins that will enable detailed analysis of a number of microbiological and physicochemical data.</p

The hidden label-marginal biases of segmentation losses

Most segmentation losses are arguably variants of the Cross-Entropy (CE) or Dice losses. In the abundant segmentation literature, there is no clear consensus as to which of these losses is a better choice, with varying performances for each across different benchmarks and applications. In this work, we develop a theoretical analysis that links these two types of losses, exposing their advantages and weaknesses. First, we provide a constrained-optimization perspective showing that CE and Dice share a much deeper connection than previously thought: They both decompose into label-marginal penalties and closely related ground-truth matching penalties. Then, we provide bound relationships and an information-theoretic analysis, which uncover hidden label-marginal biases: Dice has an intrinsic bias towards specific extremely imbalanced solutions, whereas CE implicitly encourages the ground-truth region proportions. Our theoretical results explain the wide experimental evidence in the medical-imaging literature, whereby Dice losses bring improvements for imbalanced segmentation. It also explains why CE dominates natural-image problems with diverse class proportions, in which case Dice might have difficulty adapting to different label-marginal distributions. Based on our theoretical analysis, we propose a principled and simple solution, which enables to control explicitly the label-marginal bias. Our loss integrates CE with explicit ${\cal L}_1$ regularization, which encourages label marginals to match target class proportions, thereby mitigating class imbalance but without losing generality. Comprehensive experiments and ablation studies over different losses and applications validate our theoretical analysis, as well as the effectiveness of our explicit label-marginal regularizers.Comment: Code available at https://github.com/by-liu/SegLossBia

BACTIBASE second release: a database and tool platform for bacteriocin characterization

<p>Abstract</p> <p>Background</p> <p>BACTIBASE is an integrated open-access database designed for the characterization of bacterial antimicrobial peptides, commonly known as bacteriocins.</p> <p>Description</p> <p>For its second release, BACTIBASE has been expanded and equipped with additional functions aimed at both casual and power users. The number of entries has been increased by 44% and includes data collected from published literature as well as high-throughput datasets. The database provides a manually curated annotation of bacteriocin sequences. Improvements brought to BACTIBASE include incorporation of various tools for bacteriocin analysis, such as homology search, multiple sequence alignments, Hidden Markov Models, molecular modelling and retrieval through our taxonomy Browser.</p> <p>Conclusion</p> <p>The provided features should make BACTIBASE a useful tool in food preservation or food safety applications and could have implications for the development of new drugs for medical use. BACTIBASE is available at <url>http://bactibase.pfba-lab-tun.org</url>.</p

A Foundation LAnguage-Image model of the Retina (FLAIR): Encoding expert knowledge in text supervision

Foundation vision-language models are currently transforming computer vision, and are on the rise in medical imaging fueled by their very promising generalization capabilities. However, the initial attempts to transfer this new paradigm to medical imaging have shown less impressive performances than those observed in other domains, due to the significant domain shift and the complex, expert domain knowledge inherent to medical-imaging tasks. Motivated by the need for domain-expert foundation models, we present FLAIR, a pre-trained vision-language model for universal retinal fundus image understanding. To this end, we compiled 37 open-access, mostly categorical fundus imaging datasets from various sources, with up to 97 different target conditions and 284,660 images. We integrate the expert's domain knowledge in the form of descriptive textual prompts, during both pre-training and zero-shot inference, enhancing the less-informative categorical supervision of the data. Such a textual expert's knowledge, which we compiled from the relevant clinical literature and community standards, describes the fine-grained features of the pathologies as well as the hierarchies and dependencies between them. We report comprehensive evaluations, which illustrate the benefit of integrating expert knowledge and the strong generalization capabilities of FLAIR under difficult scenarios with domain shifts or unseen categories. When adapted with a lightweight linear probe, FLAIR outperforms fully-trained, dataset-focused models, more so in the few-shot regimes. Interestingly, FLAIR outperforms by a large margin more generalist, larger-scale image-language models, which emphasizes the potential of embedding experts' domain knowledge and the limitations of generalist models in medical imaging.Comment: The pre-trained model is available at: https://github.com/jusiro/FLAI

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

Evidence for the existence of two distinct species: Psammomys obesus and Psammomys vexillaris within the sand rats (Rodentia, Gerbillinae), reservoirs of cutaneous leishmaniasis in Tunisia

International audienceA thorough taxonomic knowledge about putative animal reservoirs of transmissible diseases is an absolute prerequisite to any ecological investigation and epidemiological survey of zoonoses. Indeed, accurate identification of these reservoirs is essential for predicting species-specific population outbreaks and therefore to develop accurate ecological control strategies. The systematic status of sand rats (genus Psammomys) remains unclear despite the pivotal role of these rodents in the epidemiology of Zoonotic Cutaneous Leishmaniasis (ZCL) disease as sand rats are the main known reservoir hosts of the protozoan parasite Leishmania major. In the present work, we expose morphological, biochemical, genetic and cytogenetic evidence supporting the identification of at least two cryptic species within the genus Psammomys in Tunisia. First, significant morphometric differences were observed and were correlated associated with external features and biogeographic origins. Second, differences in patterns of two isoenzymic systems (Glutamate Oxaloacetate Transaminase (GOT) and 6-PhosphoGluconate Dehydrogenase (6PGD)) were found, which makes it possible to amount these isoenzyme characters to two diagnostic loci. Third, based on the mitochondrial cytochrome b (cyt b) gene, a high magnitude of genetic distance (13.89%) was also observed. Fourth, cytogenetic analysis showed that these two populations groups differ in their diploid chromosome numbers, i.e. 2N=46 versus 2N=48. We consider that all these variations are enough important to be considered as demonstrative and we propose that these two lineages should be considered as two distinct species that we refer to the fat sand rat Psammomys obesus Cretzschmar, 1828 and the thin sand rat Psammomys vexillaris Thomas, 1925. Implications of such results on the eco-epidemiology of ZCL in Tunisia are discussed

Patterns of infection of haemoparasites in the fat sand rat, Psammomys obesus, in Tunisia, and effect on the host

International audienceTwo bacterial and one protozoan blood parasite, belonging to the genera Bartonella, Borrelia and Babesia, were studied in a Tunisian population of Psammomys obesus. Seasonal changes in the abundance of the parasites and host were monitored in a longitudinal field survey lasting 17 months. Blood samples collected during eight rodent-trapping sessions, between September 1995 and January 1997, were examined microscopically. Bartonella sp. showed a seasonal pattern, with most transmission occurring in summer and autumn; most rodents (90%) were infected in August—September, when they were at low density and adult. Borrelia sp. showed low prevalences, with few seasonal fluctuations, and Babesia sp. showed an intermediate pattern, differing from one year to another. In the cohort of adult rats, infections with Bartonella sp. and Babesia sp. were less prevalent in winter than in the previous summer. Single and mixed infections were equally prevalent in females and males, and in sexually active and inactive adults. In addition, infection had no apparent effect on the weight of adult P. obesus. The observation that the proportion of erythrocytes infected with Bartonella sp. decreased with increasing host age is probably indicative of some acquired immunity to this micro-organism. The absence of detectable infections with Borrelia sp. in old rats indicates that the prevalence and/or intensity of infection declines with host age or that infected animals die selectively. However, there was no indication that any of these parasites combined sufficient pathogenicity and abundance to have any measurable effect on the rodent population