More Like this

1. Quorum Sensing and Antimicrobial Production Orchestrate Biofilm Dynamics in Multispecies Bacterial Communities

   https://doi.org/10.1128/spectrum.02615-22  

   Armes, April C.; Walton, Jillian L.; Buchan, Alison (October 2022, Microbiology Spectrum)

   DeAngelis, Kristen M. (Ed.)

   ABSTRACT Microbial interactions are often mediated by diffusible small molecules, including secondary metabolites, that play roles in cell-to-cell signaling and inhibition of competitors. Biofilms are often “hot spots” for high concentrations of bacteria and their secondary metabolites, which make them ideal systems for the study of small-molecule contributions to microbial interactions. Here, we use a five-member synthetic community consisting of Roseobacteraceae representatives to investigate the role of secondary metabolites on microbial biofilm dynamics. One synthetic community member, Rhodobacterales strain Y4I, possesses two acylated homoserine lactone (AHL)-based cell-to-cell signaling systems ( pgaRI and phaRI ) as well as a nonribosomal peptide synthase gene ( igi ) cluster that encodes the antimicrobial indigoidine. Through serial substitution of Y4I with mutants deficient in single signaling molecule pathways, the contribution of these small-molecule systems could be assessed. As secondary metabolite production is dependent upon central metabolites, the influence of growth substrate (i.e., complex medium versus defined medium with a single carbon substrate) on these dynamics was also considered. Depending on the Y4I mutant genotype included, community dynamics ranged from competitive to cooperative. The observed interactions were mostly competitive in nature. However, the community harboring a Y4I variant that was both impaired in quorum sensing (QS) pathways and unable to produce indigoidine ( pgaR variant) shifted toward more cooperative interactions over time. These cooperative interactions were enhanced in the defined growth medium. The results presented provide a framework for deciphering complex, small-molecule-mediated interactions that have broad application to microbial biology. IMPORTANCE Microbial biofilms play critical roles in marine ecosystems and are hot spots for microbial interactions that play a role in the development and function of these communities. Roseobacteraceae are an abundant and active family of marine heterotrophic bacteria forming close associations with phytoplankton and carrying out key transformations in biogeochemical cycles. Group members are aggressive primary colonizers of surfaces, where they set the stage for the development of multispecies biofilm communities. Few studies have examined the impact of secondary metabolites, such as cell-to-cell signaling and antimicrobial production, on marine microbial biofilm community structure. Here, we assessed the impact of secondary metabolites on microbial interactions using a synthetic, five-member Roseobacteraceae community by measuring species composition and biomass production during biofilm growth. We present evidence that secondary metabolites influence social behaviors within these multispecies microbial biofilms, thereby improving understanding of bacterial secondary metabolite production influence on social behaviors within marine microbial biofilm communities. 

   more » « less
2. Antagonism between killer yeast strains as an experimental model for biological nucleation dynamics

   https://doi.org/10.7554/eLife.62932  

   Giometto, Andrea; Nelson, David R; Murray, Andrew W (December 2021, eLife)

   Antagonistic interactions are widespread in the microbial world and affect microbial evolutionary dynamics. Natural microbial communities often display spatial structure, which affects biological interactions, but much of what we know about microbial antagonism comes from laboratory studies of well-mixed communities. To overcome this limitation, we manipulated two killer strains of the budding yeastSaccharomyces cerevisiae, expressing different toxins, to independently control the rate at which they released their toxins. We developed mathematical models that predict the experimental dynamics of competition between toxin-producing strains in both well-mixed and spatially structured populations. In both situations, we experimentally verified theory’s prediction that a stronger antagonist can invade a weaker one only if the initial invading population exceeds a critical frequency or size. Finally, we found that toxin-resistant cells and weaker killers arose in spatially structured competitions between toxin-producing strains, suggesting that adaptive evolution can affect the outcome of microbial antagonism in spatial settings. 

   more » « less
3. Recent advances of droplet-based microfluidics for engineering artificial cells

   https://doi.org/10.1016/j.slast.2023.05.002  

   Fasciano, Samantha; Wang, Shue (May 2023, SLAS Technology)

   The goal of engineering artificial cells is to build a living cell with the least amount of parts and complexity. Artificial cells hold great potential for several applications, including membrane protein interactions, gene expression, biomaterials, and drug development. It is critical to generate robust, stable artificial cells using high throughput, easy-to-control, and flexible techniques. Recently, droplet-based microfluidic techniques have shown great potential for the synthesis of vesicles and artificial cells. Here, we summarized the recent advances in droplet-based microfluidic techniques for the fabrication of vesicles and artificial cells. We first reviewed the different types of droplet-based microfluidic devices, including flow-focusing, T-junction, and coflowing. Next, we discussed the formation of multi-compartmental vesicles and artificial cells based on droplet-based microfluidics. The applications of artificial cells for studying gene expression dynamics, artificial cell-cell communications, and mechanobiology are highlighted and discussed. Finally, the current challenges and future outlook of droplet-based microfluidic methods for engineering artificial cells are discussed. This review will provide insights into scientific research in synthetic biology, microfluidic devices, membrane interactions, and mechanobiology. 

   more » « less
4. Automated Identification of Characteristic Droplet Size Distributions in Stratocumulus Clouds Utilizing a Data Clustering Algorithm

   https://doi.org/10.1175/AIES-D-22-0003.1  

   Allwayin, Nithin; Larsen, Michael L.; Shaw, Alexander G.; Shaw, Raymond A. (July 2022, Artificial Intelligence for the Earth Systems)

   Abstract Droplet-level interactions in clouds are often parameterized by a modified gamma fitted to a “global” droplet size distribution. Do “local” droplet size distributions of relevance to microphysical processes look like these average distributions? This paper describes an algorithm to search and classify characteristic size distributions within a cloud. The approach combines hypothesis testing, specifically, the Kolmogorov–Smirnov (KS) test, and a widely used class of machine learning algorithms for identifying clusters of samples with similar properties: density-based spatial clustering of applications with noise (DBSCAN) is used as the specific example for illustration. The two-sample KS test does not presume any specific distribution, is parameter free, and avoids biases from binning. Importantly, the number of clusters is not an input parameter of the DBSCAN-type algorithms but is independently determined in an unsupervised fashion. As implemented, it works on an abstract space from the KS test results, and hence spatial correlation is not required for a cluster. The method is explored using data obtained from the Holographic Detector for Clouds (HOLODEC) deployed during the Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA) field campaign. The algorithm identifies evidence of the existence of clusters of nearly identical local size distributions. It is found that cloud segments have as few as one and as many as seven characteristic size distributions. To validate the algorithm’s robustness, it is tested on a synthetic dataset and successfully identifies the predefined distributions at plausible noise levels. The algorithm is general and is expected to be useful in other applications, such as remote sensing of cloud and rain properties. Significance StatementA typical cloud can have billions of drops spread over tens or hundreds of kilometers in space. Keeping track of the sizes, positions, and interactions of all of these droplets is impractical, and, as such, information about the relative abundance of large and small drops is typically quantified with a “size distribution.” Droplets in a cloud interact locally, however, so this work is motivated by the question of whether the cloud droplet size distribution is different in different parts of a cloud. A new method, based on hypothesis testing and machine learning, determines how many different size distributions are contained in a given cloud. This is important because the size distribution describes processes such as cloud droplet growth and light transmission through clouds. 

   more » « less
5. Bioactive exometabolites drive maintenance competition in simple bacterial communities

   https://doi.org/10.1128/msystems.00064-24  

   Chodkowski, John L; Shade, Ashley (April 2024, mSystems)

   Patil, Kiran (Ed.)

   ABSTRACT During prolonged resource limitation, bacterial cells can persist in metabolically active states of non-growth. These maintenance periods, such as those experienced in stationary phase, can include upregulation of secondary metabolism and release of exometabolites into the local environment. As resource limitation is common in many environmental microbial habitats, we hypothesized that neighboring bacterial populations employ exometabolites to compete or cooperate during maintenance and that these exometabolite-facilitated interactions can drive community outcomes. Here, we evaluated the consequences of exometabolite interactions over the stationary phase among three environmental strains:Burkholderia thailandensisE264,Chromobacterium subtsugae ATCC 31532, andPseudomonas syringaepv.tomatoDC3000. We assembled them into synthetic communities that only permitted chemical interactions. We compared the responses (transcripts) and outputs (exometabolites) of each member with and without neighbors. We found that transcriptional dynamics were changed with different neighbors and that some of these changes were coordinated between members. The dominant competitorB. thailandensisconsistently upregulated biosynthetic gene clusters to produce bioactive exometabolites for both exploitative and interference competition. These results demonstrate that competition strategies during maintenance can contribute to community-level outcomes. It also suggests that the traditional concept of defining competitiveness by growth outcomes may be narrow and that maintenance competition could be an additional or alternative measure. IMPORTANCEFree-living microbial populations often persist and engage in environments that offer few or inconsistently available resources. Thus, it is important to investigate microbial interactions in this common and ecologically relevant condition of non-growth. This work investigates the consequences of resource limitation for community metabolic output and for population interactions in simple synthetic bacterial communities. Despite non-growth, we observed active, exometabolite-mediated competition among the bacterial populations. Many of these interactions and produced exometabolites were dependent on the community composition but we also observed that one dominant competitor consistently produced interfering exometabolites regardless. These results are important for predicting and understanding microbial interactions in resource-limited environments. 

   more » « less