Conferences are spaces to meet and network within and across academic and technical fields, learn about new advances, and share our work. They can help define career paths and create long-lasting collaborations and opportunities. However, these opportunities are not equal for all. This article introduces 10 simple rules to host an inclusive conference based on the authors’ recent experience organizing the 2021 edition of the useR! statistical computing conference, which attracted a broad range of participants from academia, industry, government, and the nonprofit sector. Coming from different backgrounds, career stages, and even continents, we embraced the challenge of organizing a high-quality virtual conference in the context of the Coronavirus Disease 2019 (COVID-19) pandemic and making it a kind, inclusive, and accessible experience for as many people as possible. The rules result from our lessons learned before, during, and after the organization of the conference. They have been written mainly for potential organizers and selection committees of conferences and contain multiple practical tips to help a variety of events become more accessible and inclusive. We see this as a starting point for conversations and efforts towards building more inclusive conferences across the world. * Translated versions of the English abstract and the list of rules are available in 10 languages in S1 Text: Arabic, French, German, Italian, Japanese, Korean, Portuguese, Spanish, Tamil, and Thai.

Spider venoms represent an original source of novel compounds with therapeutic and agrochemical potential. Whereas most of the research efforts have focused on large mygalomorph spiders, araneomorph spiders are equally promising but require more sensitive and sophisticated approaches given their limited size and reduced venom yield. Belonging to the latter group, the genus Lycosa (“wolf spiders”) contains many species widely distributed throughout the world. These spiders are ambush predators that do not build webs but instead rely strongly on their venom for prey capture. Lycosa tarantula is one of the largest species of wolf spider, but its venom composition is unknown. Using a combination of RNA sequencing of the venom glands and venom proteomics, we provide the first overview of the peptides and proteins produced by this iconic Mediterranean spider. Beside the typical small disulfide rich neurotoxins, several families of proteins were also identified, including cysteine-rich secretory proteins (CRISP) and Hyaluronidases. Proteomic analysis of the electrically stimulated venom validated 30 of these transcriptomic sequences, including nine putative neurotoxins and eight venom proteins. Interestingly, LC-MS venom profiles of manual versus electric stimulation, as well as female versus male, showed some marked differences in mass distribution. Finally, we also present some preliminary data on the biological activity of L. tarantula crude venom.

Despite their impressive diversity and already broad therapeutic applications, cone snail venoms have received less attention as a natural source in the investigation of antimicrobial peptides than other venomous animals such as scorpions, spiders, or snakes. Cone snails are among the largest genera (Conus sp.) of marine invertebrates, with more than seven hundred species described to date. These predatory mollusks use their sophisticated venom apparatus to capture prey or defend themselves. In-depth studies of these venoms have unraveled many biologically active peptides with pharmacological properties of interest in the field of pain management, the treatment of epilepsy, neurodegenerative diseases, and cardiac ischemia. Considering sequencing efficiency and affordability, cone snail venom gland transcriptome analyses could allow the discovery of new, promising antimicrobial peptides. We first present here the need for novel compounds like antimicrobial peptides as a viable alternative to conventional antibiotics. Secondly, we review the current knowledge on cone snails as a source of antimicrobial peptides. Then, we present the current state of the art in analytical methods applied to crude or milked venom followed by how antibacterial activity assay can be implemented for fostering cone snail antimicrobial peptides studies. We also propose a new innovative profile Hidden Markov model-based approach to annotate full venom gland transcriptomes and speed up the discovery of potentially active peptides from cone snails.

Over the past decade, many projects have been initiated worldwide to decipher the composition and function of the soil microbiome, including the African Soil Microbiome (AfSM) project that aims at providing new insights into the presence and distribution of key groups of soil bacteria from across the African continent. In this national study, carried out under the auspices of the AfSM project, we assessed the taxonomy, diversity and distribution of rhizobial genera in soils from the tropical savannah zones in Northern Côte d’Ivoire. Genomic DNA extracted from seven sampled soils was analyzed by sequencing the V4-V5 variable region of the 16S rDNA using Illumina’s MiSeq platform. Subsequent bioinformatic and phylogenetic analyses showed that these soils harbored 12 out of 18 genera of Proteobacteria harboring rhizobia species validly published to date and revealed for the first time that the Bradyrhizobium genus dominates in tropical savannah soils, together with Microvirga and Paraburkholderia. In silico comparisons of different 16S rRNA gene variable regions suggested that the V5-V7 region could be suitable for differentiating rhizobia at the genus level, possibly replacing the use of the V4-V5 region. These data could serve as indicators for future rhizobial microbiome explorations and for land-use decision-making.

Cone snails are among the richest sources of natural peptides with promising pharmacological and therapeutic applications. With the reduced costs of RNAseq, scientists now heavily rely on venom gland transcriptomes for the mining of novel bioactive conopeptides, but the bioinformatic analyses often hamper the discovery process. Here, we present ConoDictor 2.0 as a standalone and user-friendly command-line program. We have updated the program originally published as a web server 10 years ago using novel and updated tools and algorithms and improved our classification models with new and higher quality sequences. ConoDictor 2.0 is now more accurate, faster, multiplatform and able to deal with a whole cone snail venom gland transcriptome (raw reads or contigs) in a very short time. The new version of Conodictor also improves the identification and subsequent classification for entirely novel or relatively distant conopeptides. We conducted various tests on known conopeptides from public databases and on the published venom duct transcriptome of Conus geographus, and compared previous results with the output of ConoDictor 2.0, ConoSorter and BLAST. Overall, ConoDictor 2.0 is 4 to 8 times faster for the analysis of a whole transcriptome on a single core computer and performed better at predicting gene superfamily. ConoDictor 2.0 is available as a python 3 git folder at https://github.com/koualab/conodictor. Supplementary data are available at Bioinformatics Advances online.