Estimating the maximal growth rates of eukaryotic microbes from cultures and metagenomes via codon usage patterns

Microbial eukaryotes are ubiquitous in the environment and play important roles in key ecosystem processes, including accounting for a significant portion of global primary production. Yet, our tools for assessing the functional capabilities of eukaryotic microbes in the environment are quite limited because many microbes have yet to be grown in culture. Maximum growth rate is a fundamental parameter of microbial lifestyle that reveals important information about an organism's functional role in a community. We developed and validated a genomic estimator of maximum growth rate for eukaryotic microbes, enabling the assessment of growth potential for both cultivated and yet-to-be-cultivated organisms. We produced a database of over 700 growth predictions from genomes, transcriptomes, and metagenome-assembled genomes, and found that closely related and/or functionally similar organisms tended to have similar maximal growth rates. By comparing the maximal growth rates of existing culture collections with environmentally-derived genomes we found that, unlike for prokaryotes, culture collections of microbial eukaryotes are only minimally biased in terms of growth potential. We then extended our tool to make community-wide estimates of growth potential from over 500 marine metagenomes, mapping growth potential across the global oceans. We found that prokaryotic and eukaryotic communities have highly correlated growth potentials near the ocean surface, but that this relationship disappears deeper in the water column. This suggests that fast growing eukaryotes and prokaryotes thrive under similar conditions at the ocean surface, but that there is a decoupling of these communities as resources become scarce deeper in the water column.

New Types of Dissipative Streaming Instabilities

Two new, previously unknown types of dissipative streaming instabilities (DSI) are substantiated. They follow from new approach, which allows solving in general form the classical problem of an initial perturbation development for streaming instabilities (SI). SI is caused by relative motion of the streams of plasma components. With an increase in level of dissipation SI transforms into a DSI. The transformation occurs because dissipation serves as a channel for energy removal for the growth of the negative energy wave of the stream. Until recently, only one type of DSI was known. Its maximal growth rate depends on the beam density nb and the collision frequency ν in the plasma as ∼nb/ν. All types of conventional beam-plasma instabilities (Cherenkov, cyclotron, etc.) transform into it. The solution of the problem of the initial perturbation development in systems with weak beam-plasma coupling leads to a new type of DSI. With an increase in the level of dissipation, the instability in these systems transforms to the new DSI. Its maximal growth rate is ∼nb/ν. The second new DSI develops in beam-plasma waveguide with over-limiting current of e-beam. Its growth rate ∼nb/ν. In addition, the solutions of abovementioned problem provide much information about SI and DSI, significant part of which is unavailable by other methods.

Effect of genetic background on the evolution of Vancomycin-Intermediate Staphylococcus aureus (VISA)

Vancomycin-intermediate Staphylococcus aureus (VISA) typically arises through accumulation of chromosomal mutations that alter cell-wall thickness and global regulatory pathways. Genome-based prediction of VISA requires understanding whether strain background influences patterns of mutation that lead to resistance. We used an iterative method to experimentally evolve three important methicillin-resistant S. aureus (MRSA) strain backgrounds—(CC1, CC5 and CC8 (USA300)) to generate a library of 120 laboratory selected VISA isolates. At the endpoint, isolates had vancomycin MICs ranging from 4 to 10 μg/mL. We detected mutations in more than 150 genes, but only six genes (already known to be associated with VISA from prior studies) were mutated in all three background strains (walK, prs, rpoB, rpoC, vraS, yvqF). We found evidence of interactions between loci (e.g., vraS and yvqF mutants were significantly negatively correlated) and rpoB, rpoC, vraS and yvqF were more frequently mutated in one of the backgrounds. Increasing vancomycin resistance was correlated with lower maximal growth rates (a proxy for fitness) regardless of background. However, CC5 VISA isolates had higher MICs with fewer rounds of selection and had lower fitness costs than the CC8 VISA isolates. Using multivariable regression, we found that genes differed in their contribution to overall MIC depending on the background. Overall, these results demonstrated that VISA evolved through mutations in a similar set of loci in all backgrounds, but the effect of mutation in common genes differed with regard to fitness and contribution to resistance in different strains.

Diel light cycles affect phytoplankton competition in the global ocean

Light, essential for photosynthesis, is present in two periodic cycles in nature: seasonal and diel. Although seasonality of light is typically resolved in ocean ecosystem and biogeochemistry models because of its significance for seasonal succession and biogeography of phytoplankton, the diel light cycle is generally not resolved. Here we use a three-dimensional global ocean model and compare high temporal resolution simulations with and without diel light cycles. The model simulates 15 phytoplankton types of different cell size, encompassing two broad ecological strategies: small cells with high nutrient affinity (gleaners) and larger cells with high maximal growth rate (opportunists). Both are grazed by zooplankton and limited by nitrogen, phosphorus and iron. Simulations show that diel cycles of light induce diel cycles in phytoplankton populations and limiting nutrients in the global ocean. Diel nutrient cycles are associated with higher concentration of limiting nutrients by up to 200% at low latitudes (-40 to 40), a process that increases opportunists biomass by up to 50%. Size classes with the highest maximal growth rates from both gleaner and opportunist groups are favored the most by diel light cycles. This mechanism weakens as latitude increases because the effects of the seasonal cycle dominate over those of the diel cycle. The present work shows that resource competition under diel light cycles has a significant impact on phytoplankton biogeography, indicating the necessity of resolving diel processes in global ocean models.

Nutrient complexity triggers transitions between solitary and colonial growth in bacterial populations

Microbial populations often experience fluctuations in nutrient complexity in their natural environment such as between high molecular weight polysaccharides and simple monosaccharides. However, it is unclear if cells can adopt growth behaviors that allow individuals to optimally respond to differences in nutrient complexity. Here, we directly control nutrient complexity and use quantitative single-cell analysis to study the growth dynamics of individuals within populations of the aquatic bacterium Caulobacter crescentus. We show that cells form clonal microcolonies when growing on the polysaccharide xylan, which is abundant in nature and degraded using extracellular cell-linked enzymes; and disperse to solitary growth modes when the corresponding monosaccharide xylose becomes available or nutrients are exhausted. We find that the cellular density required to achieve maximal growth rates is four-fold higher on xylan than on xylose, indicating that aggregating is advantageous on polysaccharides. When collectives on xylan are transitioned to xylose, cells start dispersing, indicating that colony formation is no longer beneficial and solitary behaviors might serve to reduce intercellular competition. Our study demonstrates that cells can dynamically tune their behaviors when nutrient complexity fluctuates, elucidates the quantitative advantages of distinct growth behaviors for individual cells and indicates why collective growth modes are prevalent in microbial populations.

Estimating maximal microbial growth rates from cultures, metagenomes, and single cells via codon usage patterns

Maximal growth rate is a basic parameter of microbial lifestyle that varies over several orders of magnitude, with doubling times ranging from a matter of minutes to multiple days. Growth rates are typically measured using laboratory culture experiments. Yet, we lack sufficient understanding of the physiology of most microbes to design appropriate culture conditions for them, severely limiting our ability to assess the global diversity of microbial growth rates. Genomic estimators of maximal growth rate provide a practical solution to survey the distribution of microbial growth potential, regardless of cultivation status. We developed an improved maximal growth rate estimator and predicted maximal growth rates from over 200,000 genomes, metagenome-assembled genomes, and single-cell amplified genomes to survey growth potential across the range of prokaryotic diversity; extensions allow estimates from 16S rRNA sequences alone as well as weighted community estimates from metagenomes. We compared the growth rates of cultivated and uncultivated organisms to illustrate how culture collections are strongly biased toward organisms capable of rapid growth. Finally, we found that organisms naturally group into two growth classes and observed a bias in growth predictions for extremely slow-growing organisms. These observations ultimately led us to suggest evolutionary definitions of oligotrophy and copiotrophy based on the selective regime an organism occupies. We found that these growth classes are associated with distinct selective regimes and genomic functional potentials.

Time to Change for Mental Health and Well-being via Virtual Professional Coaching: Longitudinal Observational Study (Preprint)

BACKGROUND Optimal mental health yields many benefits and reduced costs to employees and organizations; however, the workplace introduces challenges to building and maintaining mental health that affect well-being. Although many organizations have introduced programming to aid employee mental health and well-being, the uptake and effectiveness of these efforts vary. One barrier to developing more effective interventions is a lack of understanding about how to improve well-being over time. This study examined not only whether employer-provided coaching is an effective strategy to improve mental health and well-being in employees but also how this intervention changes well-being in stages over time. OBJECTIVE The goal of this study was to determine whether BetterUp, a longitudinal one-on-one virtual coaching intervention, improves components of mental health and psychological well-being, and whether the magnitude of changes vary in stages over time. This is the first research study to evaluate the effectiveness of professional coaching through three repeated assessments, moving beyond a pre-post intervention design. The outcomes of this study will enable coaches and employers to design more targeted interventions by outlining when to expect maximal growth in specific outcomes throughout the coaching engagement. METHODS Three identical assessments were completed by 391 users of BetterUp: prior to the start of coaching, after approximately 3-4 months of coaching, and again after 6-7 months of coaching. Three scales were used to evaluate psychological and behavioral dimensions that support management of mental health: stress management, resilience, and life satisfaction. Six additional scales were used to assess psychological well-being: emotional regulation, prospection ability, finding purpose and meaning, self-awareness, self-efficacy, and social connection. RESULTS Using mixed-effects modeling, varying rates of change were observed in several dimensions of mental health and psychological well-being. Initial rapid improvements in the first half of the intervention, followed by slower growth in the second half of the intervention were found for prospection ability, self-awareness, self-efficacy, social connection, emotional regulation, and a reduction in stress (range of unstandardized β values for each assessment: .10-.19). Life satisfaction improved continuously throughout the full intervention period (β=.13). Finding purpose in meaning at work and building resilience both grew continuously throughout the coaching intervention, but larger gains were experienced in the second half of the intervention (β=.08-.18), requiring the full length of the intervention to realize maximal growth. CONCLUSIONS The results demonstrate the effectiveness of BetterUp virtual one-on-one coaching to improve psychological well-being, while mitigating threats to mental health such as excessive and prolonged stress, low resilience, and poor satisfaction with life. The improvements across the collection of outcomes were time-dependent, and provide important insights to users and practitioners about how and when to expect maximal improvements in a range of interrelated personal and professional outcomes.

PROTEIN AND ENERGY REQUIREMENTS OF BROILER CHICKENS IN THE TROPICS

An experimental design consisting of four or three protein levels and three energy levels were used to determine the optimum protein and energy requirements for starting broilers (0-6) weeks of age and finishing broilers (6-10) weeks of age. For the starting phase, four protein levels (20, 23, 24 and 26%) and three energy levels (2800, 3000 and 3200 Kcal ME/kg) were employed, while in the finishing phase three protein levels (18, 20 and 22%) and the same three energy levels as in the starting phase were used. In the two experiments growth rate and feed efficiency improved as protein level increased. The 3000 Keal ME/kg energy level appeared to be the best for maximal growth. Of the four protein levels used for the starting phase, the minimum required for growth was clearly shown to be 23% while 20% was minimum required for the finishing phase. The results of the present studies indicate that the following minimal protein and metabolizable energy levels were required for broiler chicks in the tropics: 23–24% protein with energy level of 2800-3000 Kcal ME/kg for the starting phrase and 20% protein and energy level of 2800 - 3000 Kcal ME/kg for the finishing phase.

Biological features and conditions of surface cultivating of a strain-producer of microbiopreparation Т-1 Trichoderma sp. against pathogen causing fusarium on oil flax

To develop technological regimen for production of microbiopreparations in a preparation form ‘wetting powder’ we studied biological features and conditions of surface cultivating of a strain-producer Т-1 Trichoderma sp. – an antagonist of pathogen Fusarium oxysporum Schlecht. emend. Shyd. et Hans. var. orthoceras (App. еt Wr.) Bilai and Fusarium poae (Peck) Wollenw., Lewis on oil flax. To study cultural and physiological qualities of the strainproducer we used agar and liquid mediums. Surface cultivation of a fungus on agar and liquid Rudakov’s medium at a temperature 25–30 оС was the most favorable for mycelium growth and spore formation. Stationary fungus cultivation on liquid medium with рН from 3 to 6 provided maximal mycelium growth with spore formation and the highest dry mass. Addition of starch into the Chapek’s nutrient medium caused maximal growth of fungus mycelium and increase of its dry mass. The best source of nitrogen for a fungus strain was corn extract. Rudakov’s and No1 mediums are optimal compound liquid nutrient mediums for a surface cultivation of the strain-producer. Optimal period of the surface cultivation of the fungal strain Т-1 Trichoderma sp. on liquid Rudakov’s nutrient medium was 10 days, and a volume of sowing culture to a nutrient medium – 2.0%.

Environmental and Physiological Factors Affecting High-Throughput Measurements of Bacterial Growth

ABSTRACT Bacterial growth under nutrient-rich and starvation conditions is intrinsically tied to the environmental history and physiological state of the population. While high-throughput technologies have enabled rapid analyses of mutant libraries, technical and biological challenges complicate data collection and interpretation. Here, we present a framework for the execution and analysis of growth measurements with improved accuracy over that of standard approaches. Using this framework, we demonstrate key biological insights that emerge from consideration of culturing conditions and history. We determined that quantification of the background absorbance in each well of a multiwell plate is critical for accurate measurements of maximal growth rate. Using mathematical modeling, we demonstrated that maximal growth rate is dependent on initial cell density, which distorts comparisons across strains with variable lag properties. We established a multiple-passage protocol that alleviates the substantial effects of glycerol on growth in carbon-poor media, and we tracked growth rate-mediated fitness increases observed during a long-term evolution of Escherichia coli in low glucose concentrations. Finally, we showed that growth of Bacillus subtilis in the presence of glycerol induces a long lag in the next passage due to inhibition of a large fraction of the population. Transposon mutagenesis linked this phenotype to the incorporation of glycerol into lipoteichoic acids, revealing a new role for these envelope components in resuming growth after starvation. Together, our investigations underscore the complex physiology of bacteria during bulk passaging and the importance of robust strategies to understand and quantify growth. IMPORTANCE How starved bacteria adapt and multiply under replete nutrient conditions is intimately linked to their history of previous growth, their physiological state, and the surrounding environment. While automated equipment has enabled high-throughput growth measurements, data interpretation and knowledge gaps regarding the determinants of growth kinetics complicate comparisons between strains. Here, we present a framework for growth measurements that improves accuracy and attenuates the effects of growth history. We determined that background absorbance quantification and multiple passaging cycles allow for accurate growth rate measurements even in carbon-poor media, which we used to reveal growth-rate increases during long-term laboratory evolution of Escherichia coli. Using mathematical modeling, we showed that maximum growth rate depends on initial cell density. Finally, we demonstrated that growth of Bacillus subtilis with glycerol inhibits the future growth of most of the population, due to lipoteichoic acid synthesis. These studies highlight the challenges of accurate quantification of bacterial growth behaviors.