Phenotypic and transcriptome profiling of spikes reveals the regulation of light regimens on spike growth and fertile floret number in wheat.

The spike growth phase is critical for the establishment of fertile floret (grain) numbers in wheat (Triticum aestivum L.). Then, how to shorten the spike growth phase and increase grain number synergistically? Here, we showed high-resolution analyses of floret primordia (FP) number, morphology and spike transcriptomes during the spike growth phase under three light regimens. The development of all FP in a spike could be divided into four distinct stages: differentiation (Stage I), differentiation and morphology development concurrently (Stage II), morphology development (Stage III), and polarization (Stage IV). Compared to the short photoperiod, the long photoperiod shortened spike growth and stimulated early flowering by shortening Stage III; however, this reduced assimilate accumulation, resulting in fertile floret loss. Interestingly, long photoperiod supplemented with red light shortened the time required to complete Stages I-II, then raised assimilates supply in the spike and promoted anther development before polarization initiation, thereby increasing fertile FP number during Stage III, and finally maintained fertile FP development during Stage IV until they became fertile florets via a predicted dynamic gene network. Our findings proposed a light regimen, critical stages and candidate regulators that achieved a shorter spike growth phase and a higher fertile floret number in wheat.

Three distinct metabolic phases of polychlorinated biphenyls/biphenyl degrader Acidovorax sp. KKS102 in nutrient broth.

Acidovorax sp. KKS102 is a beta-proteobacterium capable of degrading polychlorinated biphenyls (PCBs). In this study, we examined its growth in liquid nutrient broth supplemented with different carbon sources. KKS102 had at least 3 distinct metabolic phases designated as metabolic phases 1-3, with phase 2 having 2 sub-phases. For example, succinate, fumarate, and glutamate, known to repress the PCB/biphenyl catabolic operon in KKS102, were utilized in phase 1, while acetate, arabinose, and glycerol in phase 2, and glucose and mannose in phase 3. We also showed that the BphQ response regulator mediating catabolite control in KKS102, whose expression level increased moderately through the growth, plays important roles in carbon metabolism in phases 2 and 3. Our study elucidates the hierarchical growth of KKS102 in nutrient-rich media. This insight is crucial for studies exploiting microbial biodegradation capabilities and advancing studies for catabolite regulation mechanisms.

From the Microbiome to the Electrome: Implications for the Microbiota-Gut-Brain Axis.

The gut microbiome plays a fundamental role in metabolism, as well as the immune and nervous systems. Microbial imbalance (dysbiosis) can contribute to subsequent physical and mental pathologies. As such, interest has been growing in the microbiota-gut-brain brain axis and the bioelectrical communication that could exist between bacterial and nervous cells. The aim of this study was to investigate the bioelectrical profile (electrome) of two bacterial species characteristic of the gut microbiome: a Proteobacteria Gram-negative bacillus Escherichia coli (E. coli), and a Firmicutes Gram-positive coccus Enterococcus faecalis (E. faecalis). We analyzed both bacterial strains to (i) validate the fluorescent probe bis-(1,3-dibutylbarbituric acid) trimethine oxonol, DiBAC4(3), as a reliable reporter of the changes in membrane potential (Vmem) for both bacteria; (ii) assess the evolution of the bioelectric profile throughout the growth of both strains; (iii) investigate the effects of two neural-type stimuli on Vmem changes: the excitatory neurotransmitter glutamate (Glu) and the inhibitory neurotransmitter γ-aminobutyric acid (GABA); (iv) examine the impact of the bioelectrical changes induced by neurotransmitters on bacterial growth, viability, and cultivability using absorbance, live/dead fluorescent probes, and viable counts, respectively. Our findings reveal distinct bioelectrical profiles characteristic of each bacterial species and growth phase. Importantly, neural-type stimuli induce Vmem changes without affecting bacterial growth, viability, or cultivability, suggesting a specific bioelectrical response in bacterial cells to neurotransmitter cues. These results contribute to understanding the bacterial response to external stimuli, with potential implications for modulating bacterial bioelectricity as a novel therapeutic target.

Regulatory mechanism of the miR172e-LbrAP2 module during the vegetative growth phase transition in Lilium.

MAIN CONCLUSION: It was proved for the first time that the miR172e-LbrAP2 module regulated the vegetative growth phase transition in Lilium, which provided a new approach to shorten the juvenile stage of Lilium, improved the reproduction rate, and reduced the propagation cost of Lilium commercial bulbs. Lilium is an ornamental bulb plant that takes at least 3 years to cultivate into commercial seed bulbs under natural conditions. The aim of this study was to shorten the Lilium expansion cycle. In this study, the growth cycle of lily tubers induced by low temperature of 15 °C was significantly shorter than that of tubers grown at a conventional temperature. Quantitative real-time PCR analysis showed that the expression patterns of miR172e and LbrAP2 were negatively correlated. GUS histochemical staining confirmed that miR172e and LbrAP2 in tobacco leaves interacted with each other after co-transformation. The shear sites of miR172e and its target gene, LbrAP2, upon binding, were identified by RLM 5' RACE analysis. In addition, miR172e and LbrAP2 showed opposite expression patterns after the transformation of Arabidopsis. miR172e overexpression accelerated the transition from juvenile to adult plants, whereas LbrAP2 overexpression inhibited this process, thus indicating that miR172e negatively regulated the target gene LbrAP2. Upregulation of the transcription factor LbrAP2 delayed the phase transition of plants, whereas miR172 inhibited the transcriptional translation of LbrAP2, thereby accelerating the phase transition. Low-temperature treatment of Lilium bulbs can shorten Lilium development, which provides a new approach to accelerating Lilium commercial bulb breeding and reducing breeding costs.

The optimal control chart selection for monitoring COVID-19 phases: a case study of daily deaths in the USA.

Epidemiologists frequently adopt statistical process control tools, like control charts, to detect changes in the incidence or prevalence of a specific disease in real time, thereby protecting against outbreaks and emergent health concerns. Control charts have proven essential in instantly identifying fluctuations in infection rates, spotting emerging patterns, and enabling timely reaction measures in the context of COVID-19 monitoring. This study aims to review and select an optimal control chart in epidemiology to monitor variations in COVID-19 deaths and understand pandemic mortality patterns. An essential aspect of the present study is selecting an appropriate monitoring technique for distinct deaths in the USA in seven phases, including pre-growth, growth, and post-growth phases. Stage-1 evaluated control chart applications in epidemiology departments of 12 countries between 2000 and 2022. The study assessed various control charts and identified the optimal one based on maximum shift detection using sample data. This study considered at Shewhart ($\bar X$, $R$, $C$) control charts and exponentially weighted moving average (EWMA) control chart with smoothing parameters λ = 0.25, 0.5, 0.75, and 1 were all investigated in this study. In Stage-2, we applied the EWMA control chart for monitoring because of its outstanding shift detection capabilities and compatibility with the present data. Daily deaths have been monitored from March 2020 to February 2023. Control charts in epidemiology show growing use, with the USA leading at 42% applications among top countries. During the application on COVID-19 deaths, the EWMA chart accurately depicted mortality dynamics from March 2020 to February 2022, indicating six distinct stages of death. The third and fifth waves were extremely catastrophic, resulting in a considerable loss of life. Significantly, a persistent sixth wave appeared from March 2022 to February 2023. The EWMA map effectively determined the peaks associated with each wave by thoroughly examining the time and amount of deaths, providing vital insights into the pandemic's progression. The severity of each wave was measured by the average number of deaths $W5(1899)\,\gt\,W3(1881)\,\gt\,W4(1393)\,\gt\,W1(1036)\,\gt\,W2(853)\,\gt\,(W6(473)$. The USA entered a seventh phase (6th wave) from March 2022 to February 2023, marked by fewer deaths. While reassuring, it remains crucial to maintain vaccinations and pandemic control measures. Control charts enable early detection of daily COVID-19 deaths, providing a systematic strategy for government and medical staff. Incorporating the EWMA chart for monitoring immunizations, cases, and deaths is recommended.

Why Do These Yeasts Smell So Good? Volatile Organic Compounds (VOCs) Produced by Malassezia Species in the Exponential and Stationary Growth Phases.

Malassezia synthesizes and releases volatile organic compounds (VOCs), small molecules that allow them to carry out interaction processes. These lipid-dependent yeasts belong to the human skin mycobiota and are related to dermatological diseases. However, knowledge about VOC production and its function is lacking. This study aimed to determine the volatile profiles of Malassezia globosa, Malassezia restricta, and Malassezia sympodialis in the exponential and stationary growth phases. The compounds were separated and characterized in each growth phase through headspace solid-phase microextraction (HS-SPME) and gas chromatography-mass spectrometry (GC-MS). We found a total of 54 compounds, 40 annotated. Most of the compounds identified belong to alcohols and polyols, fatty alcohols, alkanes, and unsaturated aliphatic hydrocarbons. Unsupervised and supervised statistical multivariate analyses demonstrated that the volatile profiles of Malassezia differed between species and growth phases, with M. globosa being the species with the highest quantity of VOCs. Some Malassezia volatiles, such as butan-1-ol, 2-methylbutan-1-ol, 3-methylbutan-1-ol, and 2-methylpropan-1-ol, associated with biological interactions were also detected. All three species show at least one unique compound, suggesting a unique metabolism. The ecological functions of the compounds detected in each species and growth phase remain to be studied. They could interact with other microorganisms or be an important clue in understanding the pathogenic role of these yeasts.

Acetate and auto-inducing peptide are independent triggers of quorum sensing in Lactobacillus plantarum.

The synthesis of plantaricin in Lactobacillus plantarum is regulated by quorum sensing. However, the nature of the extra-cytoplasmic (EC) sensing domain of the histidine kinase (PlnB1) and the ability to recognize the auto-inducing peptide PlnA1 is not known. We demonstrate the key motif Ile-Ser-Met-Leu of auto-inducing peptide PlnA1 binds to the hydrophobic region Phe-Ala-Ser-Gln-Phe of EC loop 2 of PlnB1 via hydrophobic interactions and hydrogen bonding. Moreover, we identify a new inducer, acetate, that regulates the synthesis of plantaricin by binding to a positively charged region (Arg-Arg-Tyr-Ser-His-Lys) in loop 4 of PlnB1 via electrostatic interaction. The side chain of Phe143 on loop 4 determined the specificity and affinity of PlnB1 to recognize acetate. PlnA1 activates quorum sensing in log phase growth and acetate in stationary phase to maintain the synthesis of plantaricin under conditions of reduced growth. Acetate activation of PlnB was also evident in four types of PlnB present in different Lb. plantarum strains. Finally, we proposed a model to explain the developmental regulation of plantaricin synthesis by PlnA and acetate. These results have potential applications in improving food fermentation and bacteriocin production.

Changes in the Distribution of Membrane Lipids during Growth of Thermotoga maritima at Different Temperatures: Indications for the Potential Mechanism of Biosynthesis of Ether-Bound Diabolic Acid (Membrane-Spanning) Lipids.

Membrane-spanning lipids are present in a wide variety of archaea, but they are rarely in bacteria. Nevertheless, the (hyper)thermophilic members of the order Thermotogales harbor tetraester, tetraether, and mixed ether/ester membrane-spanning lipids mostly composed of core lipids derived from diabolic acids, C30, C32, and C34 dicarboxylic acids with two adjacent mid-chain methyl substituents. Lipid analysis of Thermotoga maritima across growth phases revealed a decrease of the relative abundance of fatty acids together with an increase of diabolic acids with independence of growth temperature. We also identified isomers of C30 and C32 diabolic acids, i.e., dicarboxylic acids with only one methyl group at C-15. Their distribution suggests they are products of the condensation reaction but are preferably produced when the length of the acyl chains is not optimal. Compared with growth at the optimal temperature of 80°C, an increase of glycerol ether-derived lipids was observed at 55°C. Our analysis only detected diabolic acid-containing intact polar lipids with phosphoglycerol (PG) head groups. Considering these findings, we hypothesize a biosynthetic pathway for the synthesis of membrane-spanning lipids based on PG polar lipid formation, suggesting that the protein catalyzing this process is a membrane protein. We also identified, by genomic and protein domain analyses, a gene coding for a putative plasmalogen synthase homologue in T. maritima that is also present in other bacteria producing sn-1-alkyl ether lipids but not plasmalogens, suggesting it is involved in the conversion of the ester-to-ether bond in the diabolic acids bound in membrane-spanning lipids. IMPORTANCE Membrane-spanning lipids are unique compounds found in most archaeal membranes, but they are also present in specific bacterial groups like the Thermotogales. The synthesis and physiological role of membrane-spanning lipids in bacteria represent an evolutionary and biochemical open question that points to the differentiation of the membrane lipid composition. Understanding the formation of membrane-spanning lipids is crucial to solving this question and identifying the enzymatic and biochemical mechanism performing this procedure. In the present work, we found changes at the core lipid level, and we propose that the growth phase drives the biosynthesis of these lipids rather than temperature. Our results identified physiological conditions influencing the membrane-spanning lipid biosynthetic process, which can further clarify the pathway leading to the biosynthesis of these compounds.

Transcriptome analysis revealed growth phase-associated changes of a centenarian-originated probiotic Bifidobacterium animalis subsp. lactis A6.

BACKGROUND: The physiology and application characteristics of probiotics are closely associated with the growth phase. Bifidobacterium animalis subsp. lactis A6 is a promising probiotic strain isolated from the feces of a healthy centenarian in China. In this study, RNA-seq was carried out to investigate the metabolic mechanism between the exponential and the stationary phase in B. lactis A6. RESULTS: Differential expression analysis showed that a total of 815 genes were significantly changed in the stationary phase compared to the exponential phase, which consisted of 399 up-regulated and 416 down-regulated genes. The results showed that the transport and metabolism of cellobiose, xylooligosaccharides and raffinose were enhanced at the stationary phase, which expanded carbon source utilizing profile to confront with glucose consumption. Meanwhile, genes involved in cysteine-cystathionine-cycle (CCC) pathway, glutamate dehydrogenase, branched-chain amino acids (BCAAs) biosynthesis, and Clp protease were all up-regulated in the stationary phase, which may enhance the acid tolerance of B. lactis A6 during stationary phase. Acid tolerance assay indicated that the survival rate of stationary phase cells was 51.07% after treatment by pH 3.0 for 2h, which was 730-fold higher than that of 0.07% with log phase cells. In addition, peptidoglycan biosynthesis was significantly repressed, which is comparable with the decreased growth rate during the stationary phase. Remarkably, a putative gene cluster encoding Tad pili was up-regulated by 6.5 to 12.1-fold, which is consistent with the significantly increased adhesion rate to mucin from 2.38% to 4.90% during the transition from the exponential phase to the stationary phase. CONCLUSIONS: This study reported growth phase-associated changes of B. lactis A6 during fermentation, including expanded carbon source utilizing profile, enhanced acid tolerance, and up-regulated Tad pili gene cluster responsible for bacterial adhesion in the stationary phase. These findings provide a novel insight into the growth phase associated characteristics in B. lactis A6 and provide valuable information for further application in the food industry.

Impact of Growth Phase, Pigment Adaptation, and Climate Change Conditions on the Cellular Pigment and Carbon Content of Fifty-One Phytoplankton Isolates.

Owing to their importance in aquatic ecosystems, the demand for models that estimate phytoplankton biomass and community composition in the global ocean has increased over the last decade. Moreover, the impacts of climate change, including elevated carbon dioxide (CO2 ), increased stratification, and warmer sea surface temperatures, will likely shape phytoplankton community composition in the global ocean. Chemotaxonomic methods are useful for modeling phytoplankton community composition from marker pigments normalized to chlorophyll a (Chl a). However, photosynthetic pigments, particularly Chl a, are sensitive to nutrient and light conditions. Cellular carbon is less sensitive, so using carbon biomass instead may provide an alternative approach. To this end, cellular pigment and carbon concentrations were measured in 51 strains of globally relevant, cultured phytoplankton. Pigment-to-Chl a and pigment-to-carbon ratios were computed for each strain. For 25 strains, measurements were taken during two growth phases. While some differences between growth phases were observed, they did not exceed within-class differences. Multiple strains of Amphidinium carterae, Ditylum brightwellii and Heterosigma akashiwo were measured to determine whether time in culture influenced pigment and carbon composition. No appreciable trends in cellular pigment or carbon content were observed. Lastly, the potential impact of climate change conditions on the pigment ratios was assessed using a multistressor experiment that included increased mean light, temperature, and elevated pCO2 on three species: Thalassiosira oceanica, Ostreococcus lucimarinus, and Synechococcus. The largest differences were observed in the pigment-to-carbon ratios, while the marker pigments largely covaried with Chl a. The implications of these observations to chemotaxonomic applications are discussed.

Physiological and microbiological hormesis in sedge Eleocharis palustris induced by crude oil in phytoremediation of flooded clay soil.

Soil contamination with petroleum hydrocarbons affects plants and rhizospheric microorganisms. Microbial activity participates in important biochemical processes that stimulate, together with plants, the modification of toxic compounds for organisms. A nine-month experiment was set up to study the effect over time of oil on plant height (cm), formation of new plants, plant matter production (gravimetry), and population of rhizospheric microorganisms (serial dilution) in the sedge Eleocharis palustris. Removal of total petroleum hydrocarbons (soxhlet and gravimetry) from the soil was also evaluated. The means of the evaluated variables registered significant statistical differences (Duncan, p < 0.05) regarding the age of the plant and the amount of crude oil. There was a high correlation between oil and plant height (0.848) and with new plants (0.994). 60 mg oil dose promoted the greatest statistical difference in the amounts of roots and plant biomass (p < 0.05). E. palustris exposed to 60 and 75 mg of oil stimulated high densities of microalgae, actinomycetes, fungi, hydrocarbonoclastic bacteria and Pseudomonas spp; the overall ratio was 2:1 relative to natural attenuation. Plant and microorganism variables evaluated registered physiological and microbiological hormetic indices ≥1, showing a positive linear relationship. Natural attenuation was more efficient in removing crude oil. We conclude that E. palustris is tolerant to oil exposure. It is suggested to combine it with natural attenuation for the optimization of soils contaminated with crude oil.

Reconstruction of transcriptional regulatory networks of Fis and H-NS in Escherichia coli from genome-wide data analysis.

Fis (Factor for inversion stimulation) and H-NS (Histone-like nucleoid-structuring protein) are two well-known nucleoid-associated proteins (NAPs) in proteobacteria, which play crucial roles in genome organization and transcriptional regulation. We performed RNA-sequencing to identify genes regulated by these NAPs. Study reveals that Fis and H-NS affect expression of 462 and 88 genes respectively in Escherichia coli at mid-exponential growth phase. By integrating available ChIP-seq data, we identified direct and indirect regulons of Fis and H-NS proteins. Functional analysis reveals that Fis controls expression of genes involved in translation, oxidative phosphorylation, sugar metabolism and transport, amino acid metabolism, bacteriocin transport, cell division, two-component system, biofilm formation, pilus organization and lipopolysaccharide biosynthesis pathways. However, H-NS represses expression of genes in cell adhesion, recombination, biofilm formation and lipopolysaccharide biosynthesis pathways under mid-exponential growth condition. The current regulatory networks thus provide a global glimpse of coordinated regulatory roles for these two important NAPs.

Prediction of Crop Yield Using Phenological Information Extracted from Remote Sensing Vegetation Index.

Phenology is an indicator of crop growth conditions, and is correlated with crop yields. In this study, a phenological approach based on a remote sensing vegetation index was explored to predict the yield in 314 counties within the US Corn Belt, divided into semi-arid and non-semi-arid regions. The Moderate Resolution Imaging Spectroradiometer (MODIS) data product MOD09Q1 was used to calculate the normalized difference vegetation index (NDVI) time series. According to the NDVI time series, we divided the corn growing season into four growth phases, calculated phenological information metrics (duration and rate) for each growth phase, and obtained the maximum correlation NDVI (Max-R2). Duration and rate represent crop growth days and rate, respectively. Max-R2 is the NDVI value with the most significant correlation with corn yield in the NDVI time series. We built three groups of yield regression models, including univariate models using phenological metrics and Max-R2, and multivariate models using phenological metrics, and multivariate models using phenological metrics combined with Max-R2 in the whole, semi-arid, and non-semi-arid regions, respectively, and compared the performance of these models. The results show that most phenological metrics had a statistically significant (p < 0.05) relationship with corn yield (maximum R2 = 0.44). Models established with phenological metrics realized yield prediction before harvest in the three regions with R2 = 0.64, 0.67, and 0.72. Compared with the univariate Max-R2 models, the accuracy of models built with Max-R2 and phenology metrics improved. Thus, the phenology metrics obtained from MODIS-NDVI accurately reflect the corn characteristics and can be used for large-scale yield prediction. Overall, this study showed that phenology metrics derived from remote sensing vegetation indexes could be used as crop yield prediction variables and provide a reference for data organization and yield prediction with physical crop significance.

Keeping Track of Phaeodactylum tricornutum (Bacillariophyta) Culture Contamination by Potentiometric E-Tongue.

The large-scale cultivation of microalgae provides a wide spectrum of marketable bioproducts, profitably used in many fields, from the preparation of functional health products and feed supplement in aquaculture and animal husbandry to biofuels and green chemistry agents. The commercially successful algal biomass production requires effective strategies to maintain the process at desired productivity and stability levels. Hence, the development of effective early warning methods to timely indicate remedial actions and to undertake countermeasures is extremely important to avoid culture collapse and consequent economic losses. With the aim to develop an early warning method of algal contamination, the potentiometric E-tongue was applied to record the variations in the culture environments, over the whole growth process, of two unialgal cultures, Phaeodactylum tricornutum and a microalgal contaminant, along with those of their mixed culture. The E-tongue system ability to distinguish the cultures and to predict their growth stage, through the application of multivariate data analysis, was shown. A PLS regression method applied to the E-tongue output data allowed a good prediction of culture growth time, expressed as growth days, with R2 values in a range from 0.913 to 0.960 and RMSEP of 1.97-2.38 days. Moreover, the SIMCA and PLS-DA techniques were useful for cultures contamination monitoring. The constructed PLS-DA model properly discriminated 67% of cultures through the analysis of their growth media, i.e., environments, thus proving the potential of the E-tongue system for a real time monitoring of contamination in microalgal intensive cultivation.

A novel mechanism of ribonuclease regulation: GcvB and Hfq stabilize the mRNA that encodes RNase BN/Z during exponential phase.

RNase BN, the Escherichia coli RNase Z family member, plays a limited role in tRNA metabolism, in contrast to most other organisms. However, RNase BN does act on 6S RNA, the global transcription regulator, degrading it in exponential-phase cells and maintaining it at low levels during this phase of growth. RNase BN levels decrease in stationary-phase cells, leading to elevation of 6S RNA and subsequent regulation of RNA polymerase. These findings were the first indication that RNase BN itself is growth phase-regulated. Here, we analyze the mechanism of this regulation of RNase BN. We find that RNase BN decreases in stationary phase because its mRNA becomes unstable, due primarily to its degradation by RNase E. However, in exponential-phase cells rbn mRNA is stabilized due to binding by the sRNA, GcvB, and the protein, Hfq, which reduce cleavage by RNase E. Because the amount of GcvB decreases in stationary phase, rbn mRNA is less protected and becomes increasingly unstable resulting in reduction in the amount of RNase BN. The small RNA-dependent, positive regulation of RNase BN in exponential-phase cells is the first example of this novel mechanism for RNase regulation.

The Conjugation Window in an Escherichia coli K-12 Strain with an IncFII Plasmid.

Many studies have examined the role that conjugation plays in disseminating antibiotic resistance genes in bacteria. However, relatively little research has quantitively examined and modeled the dynamics of conjugation under growing and nongrowing conditions beyond a couple of hours. We therefore examined growing and nongrowing cultures of Escherichia coli over a 24-h period to understand the dynamics of bacterial conjugation in the presence and absence of antibiotics with pUUH239.2, an IncFII plasmid containing multiantibiotic- and metal-resistant genes. Our data indicate that conjugation occurs after E. coli cells divide and before they have transitioned to a nongrowing phase. The result is that there is only a small window of opportunity for E. coli to conjugate with pUUH239.2 under both growing and nongrowing conditions. Only a very small percentage of the donor cells likely are capable of even undergoing conjugation, and not all transconjugants can become donor cells due to molecular regulatory controls and not being in the correct growth phase. Once a growing culture enters stationary phase, the number of capable donor cells decreases rapidly and conjugation slows to produce a plateau. Published models did not provide accurate descriptions of conjugation under nongrowing conditions. We present here a modified modeling approach that accurately describes observed conjugation behavior under growing and nongrowing conditions.IMPORTANCE There has been growing interest in horizontal gene transfer of antibiotic resistance plasmids as the antibiotic resistance crisis has worsened over the years. Most studies examining conjugation of bacterial plasmids focus on growing cultures of bacteria for short periods, but in the environment, most bacteria grow episodically and at much lower rates than in the laboratory. We examined conjugation of an IncFII antibiotic resistance plasmid in E. coli under growing and nongrowing conditions to understand the dynamics of conjugation under which the plasmid is transferred. We found that conjugation occurs in a narrow time frame when E. coli is transitioning from a growing to nongrowing phase and that the conjugation plateau develops because of a lack of capable donor cells in growing cultures. From an environmental aspect, our results suggest that episodic growth in nutrient-depleted environments could result in more conjugation than sustained growth in a nutrient rich environment.

Discriminating Bacterial Phenotypes at the Population and Single-Cell Level: A Comparison of Flow Cytometry and Raman Spectroscopy Fingerprinting.

Investigating phenotypic heterogeneity can help to better understand and manage microbial communities. However, characterizing phenotypic heterogeneity remains a challenge, as there is no standardized analysis framework. Several optical tools are available, such as flow cytometry and Raman spectroscopy, which describe optical properties of the individual cell. In this work, we compare Raman spectroscopy and flow cytometry to study phenotypic heterogeneity in bacterial populations. The growth stages of three replicate Escherichia coli populations were characterized using both technologies. Our findings show that flow cytometry detects and quantifies shifts in phenotypic heterogeneity at the population level due to its high-throughput nature. Raman spectroscopy, on the other hand, offers a much higher resolution at the single-cell level (i.e., more biochemical information is recorded). Therefore, it can identify distinct phenotypic populations when coupled with analyses tailored toward single-cell data. In addition, it provides information about biomolecules that are present, which can be linked to cell functionality. We propose a computational workflow to distinguish between bacterial phenotypic populations using Raman spectroscopy and validated this approach with an external data set. We recommend using flow cytometry to quantify phenotypic heterogeneity at the population level, and Raman spectroscopy to perform a more in-depth analysis of heterogeneity at the single-cell level. © 2019 International Society for Advancement of Cytometry.

Inference of the generalized-growth model via maximum likelihood estimation: A reflection on the impact of overdispersion.

Recently, the generalized-growth model was introduced as a flexible approach to characterize growth dynamics of disease outbreaks during the early ascending phase. In this work, by using classical maximum likelihood estimation to obtain parameter estimates, we evaluate the impact of varying levels of overdispersion on the inference of the growth scaling parameter through comparing Poisson and Negative binomial models. In particular, under exponential and sub-exponential growth scenarios, we evaluate, via simulations, the error rate of making an incorrect characterization of early outbreak growth patterns. Simulation results show that the ability to correctly identify early outbreak growth patterns can be affected by overdispersion even when accounted for using the Negative binomial model. We exemplify our findings using data on five different outbreaks. Overall, our results show that estimates should be interpreted with caution when data are overdispersed.

Engineering a growth-phase-dependent biosynthetic pathway for carotenoid production in Saccharomyces cerevisiae.

Metabolic engineering is usually focused on static control of microbial cell factories to efficient production of interested chemicals, though heterologous pathways compete with endogenous metabolism. However, products like carotenoids may cause metabolic burden on engineering strains, thus limiting product yields and influencing strain growth. Herein, a growth-phase-dependent regulation was developed to settle this matter, and its efficiency was verified using the heterogenous biosynthesis of lycopene in Saccharomyces cerevisiae as an example. Through growth-phase-dependent control of the lycopene biosynthetic pathway, limited step in MVA pathway, and competitive squalene pathway, production yield was increased by approximately 973-fold (from 0.034- to 33.1-mg/g CDW) and 1.48 g/L of production was obtained by one-stage fermentation in a 5-L bioreactor. Our study not only introduces an economically approach to the production of carotenoids, but also provides an example of dynamic regulation of biosynthetic pathways for metabolic engineering.

Vibrational Spectroscopy as a Sensitive Probe for the Chemistry of Intra-Phase Bacterial Growth.

Bacterial growth in batch cultures occurs in four phases (lag, exponential/log, stationary and death phase) that differ distinctly in number of different bacteria, biochemistry and physiology. Knowledge regarding the growth phase and its kinetics is essential for bacterial research, especially in taxonomic identification and monitoring drug interactions. However, the conventional methods by which to assess microbial growth are based only on cell counting or optical density, without any insight into the biochemistry of cells or processes. Both Raman and Fourier transform infrared (FTIR) spectroscopy have shown potential to determine the chemical changes occurring between different bacterial growth phases. Here, we extend the application of spectroscopy and for the first time combine both Raman and FTIR microscopy in a multimodal approach to detect changes in the chemical compositions of bacteria within the same phase (intra-phase). We found a number of spectral markers associated with nucleic acids (IR: 964, 1082, 1215 cm-1; RS: 785, 1483 cm-1), carbohydrates (IR: 1035 cm-1; RS: 1047 cm-1) and proteins (1394 cm-1, amide II) reflecting not only inter-, but also intra-phase changes in bacterial chemistry. Principal component analysis performed simultaneously on FTIR and Raman spectra enabled a clear-cut, time-dependent discrimination between intra-lag phase bacteria probed every 30 min. This demonstrates the unique capability of multimodal vibrational spectroscopy to probe the chemistry of bacterial growth even at the intra-phase level, which is particularly important for the lag phase, where low bacterial numbers limit conventional analytical approaches.