Plant pathogens challenge our efforts to maximize crop production due to their ability to rapidly develop resistance to pesticides. Fungal biocontrol agents have become an important alternative to chemical fungicides, due to environmental concerns related to the latter. Here we review the complex modes of action of biocontrol agents in general and epiphytic yeasts belonging to the genus Pseudozyma specifically and P. aphidis in particular. Biocontrol agents act through multiple direct and indirect mechanisms, which are mainly based on their secretions. We discuss the direct modes of action, such as antibiosis, reactive oxygen species-producing, and cell wall-degrading enzyme secretions which can also play a role in mycoparasitism. In addition, we discuss indirect modes of action, such as hyperbiotrophy, induced resistance and growth promotion based on the secretion of effectors and elicitors from the biocontrol agent. Due to their unique characteristics, epiphytic yeasts hold great potential for use as biocontrol agents, which may be more environmentally friendly than conventional pesticides and provide a way to reduce our dependency on fungicides based on increasingly expensive fossil fuels. No less important, the complex mode of action of Pseudozyma-based biocontrol agents can also reduce the frequency of resistance developed by pathogens to these agents.

The phyllosphere - the aerial parts of plants - is an important microbial habitat that is home to diverse microbial communities. The spatial organization of bacterial cells on leaf surfaces is non-random, and correlates with leaf microscopic features. Yet, the role of microscale interactions between bacterial cells therein is not well understood. Here, we ask how interactions between immigrant bacteria and resident microbiota affect the spatial organization of the combined community. By means of live imaging in a simplified in vitro system, we studied the spatial organization, at the micrometer scale, of the biocontrol agentPseudomonas fluorescensA506 and the plant pathogenP. syringaeB728a when introduced to pear and bean leaf microbiota (the corresponding native plants of these strains). We found significant co-localization of immigrant and resident microbial cells at distances of a few micrometers, for both strains. Interestingly, this co-localization was in part due to preferential attachment of microbiota cells near newly formedP. fluorescensaggregates. Our results indicate that two-way immigrant bacteria - resident microbiota interactions affect the microscale spatial organization of leaf microbiota, and possibly that of other surface-related microbial communities.

Diverse antibiotic compounds are abundant in microbial habitats undergoing recurrent wet-dry cycles, such as soil, root and leaf surfaces, and the built environment. These antibiotics play a central role in microbial warfare and competition, thus affecting population dynamics and the composition of natural microbial communities. Yet, the impact of wet-dry cycles on bacterial response to antibiotics has been scarcely explored. Using the bacterium E. coli as a model organism, we show through a combination of experiments and computational modeling, that wet-dry cycles protect bacteria from beta-lactams. This is due to the combined effect of several mechanisms including tolerance induced by high salt concentrations and slow cell-growth, which are inherently associated with microscopic surface wetness-a hydration state typical to `dry' periods. Moreover, we find evidence for a cross-protection effect, where lethal doses of antibiotic considerably increase bacterial survival during the dry periods. This work focuses on beta-lactams, yet similar protection was observed for additional major antibiotic classes. Our findings shed new light on how we understand bacterial response to antibiotics, with broad implications for population dynamics, interspecies interactions, and the evolution of antibiotic resistance in vast terrestrial microbial habitats.

Bacteria are social organisms that interact extensively within and between species while responding to external stimuli from their environments. Designing synthetic microbial communities can enable efficient and beneficial microbiome implementation in many areas. However, in order to design an efficient community, one must consider the interactions between their members. Using a reductionist approach, we examined pairwise interactions of three related Pseudomonas species in various microenvironments including plant roots and inert surfaces. Our results show that the step between monoculture and co-culture is already very complex. Monoculture root colonization patterns demonstrate that each isolate occupied a particular location on wheat roots, such as root tip, distance from the tip, or scattered along the root. However, pairwise colonization outcomes on the root did not follow the bacterial behavior in monoculture, suggesting various interaction patterns. In addition, we show that interspecies interactions on a microscale on inert surface take part in co-culture colonization and that the interactions are affected by the presence of root extracts and depend on its source. The understanding of interrelationships on the root may contribute to future attempts to manipulate and improve bacterial colonization and to intervene with root microbiomes to construct and design effective synthetic microbial consortia.

Plasmids are mobile genetic elements that play a key role in microbial ecology and evolution by mediating horizontal transfer of important genes, such as antimicrobial resistance genes. Many microbial genomes have been sequenced by short read sequencers and have resulted in a mix of contigs that derive from plasmids or chromosomes. New tools that accurately identify plasmids are needed to elucidate new plasmid-borne genes of high biological importance. We have developed Deeplasmid, a deep learning tool for distinguishing plasmids from bacterial chromosomes based on the DNA sequence and its encoded biological data. It requires as input only assembled sequences generated by any sequencing platform and assembly algorithm and its runtime scales linearly with the number of assembled sequences. Deeplasmid achieves an AUC–ROC of over 89%, and it was more accurate than five other plasmid classification methods. Finally, as a proof of concept, we used Deeplasmid to predict new plasmids in the fish pathogen Yersinia ruckeri ATCC 29473 that has no annotated plasmids. Deeplasmid predicted with high reliability that a long assembled contig is part of a plasmid. Using long read sequencing we indeed validated the existence of a 102 kb long plasmid, demonstrating Deeplasmid's ability to detect novel plasmids.

The extracellular Contractile Injection System (eCIS) is a toxin-delivery particle that evolved from a bacteriophage tail. Four eCISs have previously been shown to mediate interactions between bacteria and their invertebrate hosts. Here, we identify eCIS loci in 1,249 bacterial and archaeal genomes and reveal an enrichment of these loci in environmental microbes and their apparent absence from mammalian pathogens. We show that 13 eCIS-associated toxin genes from diverse microbes can inhibit the growth of bacteria and/or yeast. We identify immunity genes that protect bacteria from self-intoxication, further supporting an antibacterial role for some eCISs. We also identify previously undescribed eCIS core genes, including a conserved eCIS transcriptional regulator. Finally, we present our data through an extensive eCIS repository, termed eCIStem. Our findings support eCIS as a toxin-delivery system that is widespread among environmental prokaryotes and likely mediates antagonistic interactions with eukaryotes and other prokaryotes.

Managing and engineering microbial communities relies on the ability to predict their composition. While progress has been made on predicting compositions on short, ecological timescales, there is still little work aimed at predicting compositions on evolutionary timescales. Therefore, it is still unknown for how long communities typically remain stable after reaching ecological equilibrium, and how repeatable and predictable are changes when they occur. Here, we address this knowledge gap by tracking the composition of 87 two- and three-species bacterial communities, with 3–18 replicates each, for ~400 generations. We find that community composition typically changed during evolution, but that the composition of replicate communities remained similar. Furthermore, these changes were predictable in a bottom-up approach—changes in the composition of trios were consistent with those that occurred in pairs during coevolution. Our results demonstrate that simple assembly rules can hold even on evolutionary timescales, suggesting it may be possible to forecast the evolution of microbial communities.