Microbial Growth Curves: What the Models Tell Us and What They Cannot

The aroma transformation of Japanese sea bass (Lateolabrax japonicas) through endogenous enzyme incubation during the lag phase of attached microorganisms

Endogenous enzymes play a crucial role in determining fish product aroma. However, the attached microorganisms can promote enzyme production, making it challenging to identify specific aromatic compounds resulting from endogenous enzymes. Thus, we investigated the aroma transformation of Japanese sea bass through enzymatic incubation by controlling attached microorganisms during the lag phase. Our results demonstrate that enzymatic incubation significantly enhances grassy and sweet notes while reducing fishy odors. These changes in aroma are associated with increased levels of 10 volatile compounds and decreased levels of 3 volatile compounds. Among them, previous studies have reported enzyme reaction pathways for octanal, 1-nonanal, vanillin, indole, linalool, geraniol, citral, and 6-methyl-5-hepten-2-one; however, the enzymatic reaction pathways for germacrene D, beta-caryophyllene, pristane, 1-tetradecene and trans-beta-ocimene remain unclear. These findings provide novel insights for further study to elucidate the impact of endogenous enzymes on fish product aromas.

A stochastic model for the bacterial growth exhibiting staged growth, desynchronization, saturation and persistence

We consider a model of population growth based on the stochastic variation of the population size-controlled duplication of bacterial cells. It is shown that the proper choice of the control function allows for reproducing a variety of regimes: a logistic growth with saturation, a hindered growth typical for persistent bacterial systems, and a linear population growth detected for some mycobacterial populations. When supplied with the rectangular function having the width equal to the generation time, this approach represents the solution generalizing Rubinow's age-maturity model reproducing systems with desynchronisation and saturation. The model's plausibility is confirmed by the direct comparison with real data for the growth of M. tuberculosis populations obtained with the BACTEC MGIT system under different conditions of growth synchronisation.

Determination of bisphosphonate properties in terms of bioavailability, bone affinity, and cytotoxicity

BACKGROUND

The study aimed to evaluate the therapeutic potential of fourteen newly synthesized bisphosphonates by assessing their bioavailability, bone affinity, and cytotoxicity. These bisphosphonates included a series of aminomethylenebisphosphonates and standard compounds such as risedronate and tiludronate.

METHODS

Drug permeability was determined using Parallel Artificial Membrane Permeability Assays (PAMPA), while bone affinity was assessed by sorption on hydroxyapatite. Bacterial cell response to the bisphosphonates was also examined using Lactobacillus paracasei cells as a model.

RESULTS

Several tested compounds, including BP3 to BP8 and BP11, which feature substituents in the pyridine ring such as methyl groups, iodine, bromine, chlorine, or hydroxyl groups, demonstrated potentially more beneficial therapeutic properties than commercially used bisphosphonates. These compounds showed stronger bone affinity and higher gastrointestinal absorption with comparable or lower cytotoxic effects. Specifically, BP11 exhibited the highest bone affinity, while BP8 and BP11 showed the greatest permeability.

CONCLUSIONS

The findings suggest that BP3 BP8, and BP11 are promising candidates for further research. These results highlight the importance of comprehensively evaluating bisphosphonates' therapeutic properties to identify effective treatments for osteoporosis and other bone diseases.

Unraveling the impact of pH, sodium concentration, and medium osmolality on Vibrio natriegens in batch processes

BACKGROUND

Vibrio natriegens, a halophilic marine γ-proteobacterium, holds immense biotechnological potential due to its remarkably short generation time of under ten minutes. However, the highest growth rates have been primarily observed on complex media, which often suffer from batch-to-batch variability affecting process stability and performance. Consistent bioprocesses necessitate the use of chemically defined media, which are usually optimized for fermenters with pH and dissolved oxygen tension (DOT) regulation, both of which are not applied during early-stage cultivations in shake flasks or microtiter plates. Existing studies on V. natriegens' growth on mineral media report partially conflicting results, and a comprehensive study examining the combined effects of pH buffering, sodium concentration, and medium osmolality is lacking.

RESULTS

This study evaluates the influence of sodium concentration, pH buffering, and medium osmolality on the growth of V. natriegens under unregulated small-scale conditions. The maximum growth rate, time of glucose depletion, as well as the onset of stationary phase were observed through online-monitoring the oxygen transfer rate. The results revealed optimal growth conditions at an initial pH of 8.0 with a minimum of 300 mM MOPS buffer for media containing 20 g/L glucose or 180 mM MOPS for media with 10 g/L glucose. Optimal sodium chloride supplementation was found to be between 7.5 and 15 g/L, lower than previously reported ranges. This is advantageous for reducing industrial corrosion issues. Additionally, an osmolality range of 1 to 1.6 Osmol/kg was determined to be optimal for growth. Under these optimized conditions, V. natriegens achieved a growth rate of 1.97 ± 0.13 1/h over a period of 1 h at 37 °C, the highest reported rate for this organism on a mineral medium.

CONCLUSION

This study provides guidelines for cultivating V. natriegens in early-stage laboratory settings without pH and DOT regulation. The findings suggest a lower optimal sodium chloride range than previously reported and establish an osmolality window for optimal growth, thereby advancing the understanding of V. natriegens' physiology. In addition, this study offers a foundation for future research into the effects of different ions and carbon sources on V. natriegens.

Mechanistic insights into the changes of biological activity and physicochemical characteristics in Lacticaseibacillus paracasei fortified milk powder during storage

To clarify the change mechanism of biological activity and physicochemical characteristics in Lacticaseibacillus paracasei JY025 fortified milk powder (LFMP) during storage, morphological observation, JY025 survival, storage stability, and metabolomics of LFMP were determined during the storage period in this study. The results showed that the LFMP had a higher survival rate of JY025 compared with the bacterial powder of JY025 (LBP) during storage, which suggested that milk powder matrix could reduce strain JY025 mortality under prolonged storage in the LFMP samples. The fortification of strain JY025 also affected the stability of milk powder during the storage period. There was lower water activity and higher glass transition temperature in LFMP samples compared with blank control milk powder (BCMP) during storage. Moreover, the metabolomics results of LFMP indicated that vitamin degradation, Maillard reaction, lipid oxidation, tricarboxylic acid cycle, and lactobacilli metabolism are interrelated and influence each other to create complicated metabolism networks.

Multipoint monitor of beer fermentation

This short communication is devoted to a fully-mechanized flow analysis system for the control of beer fermentation process. The developed system is based on microsolenoid flow controlling devices (valves and pumps) and a flow-through optoelectronic detector. All these components are powered and controlled by a Adruino-compatible microprocessor platform that creates an integrated, compact, and robust analytical tool. Multiplication of sample aspiration ports of the analytical system allows for simultaneous monitoring of several independently performed fermentation processes, as well as a single process at the different places of fermentation tank. To demonstrate its practical utility, the developed system has been applied for online and real-time monitoring of yeast propagation and distribution in beer worts in the course of various fermentation processes. Potentially, this flow analysis system can be easily expanded to the form of multianalyte monitor equipped with optoelectronic sensors and biosensors for the determination of other parameters and analytes.

Pharmacokinetic and Pharmacodynamic Modeling Analysis of Delpazolid (LCB01-0371) in Adult Patients with Pulmonary Tuberculosis

Delpazolid (LCB01-0371) is a novel oxazolidinone derivative with a good safety profile for treating gram-positive pathogenic infections such as Mycobacterium abscessus, a highly pathogenic drug-resistant Mycobacterium. In this study, we evaluated the pharmacokinetics (PK) and pharmacodynamics (PD) of delpazolid after 14 days of multiple oral administration, using data from adult patients with pulmonary tuberculosis. 800 mg once a day, 400 mg twice a day, 800 mg twice a day, and 1200 mg once a day delpazolid for 14 days were tested in 63 patients with pulmonary tuberculosis. For PK blood collection, inpatient and outpatient scheduling were separately implemented. Plasma concentrations of delpazolid were measured at visits 2, 4, 6, and 8 in outpatients, and four sparse blood samples were measured in inpatients. PD models were sequentially fitted using individual PK parameter estimates obtained from PK compartmental models. For PK modeling, 180 plasma concentrations of delpazolid from 56 patients were included. A two-compartment mixed first- and zero-order absorption model best described the time course of plasma concentration. For the PD model, 448 bacterial titer data from 60 patients were used. The time course of bacterial titers (log10 CFU/mL) was described by a model that consists of the growth and killing rate of bacteria with the sigmoid Emax model. The PK-PD simulation suggested that the bacterial titers are the lowest on the 800 mg bid regimen among the four, consistent with observed data, as all regimens substantially decrease. In the dose-response relationship, the effectiveness of delpazolid was suggested.

Antifungal Activity, Mode of Action, and Cytotoxicity of 4-Chlorobenzyl p-Coumarate: A Promising New Molecule

Fungal infections represent a serious health problem worldwide. The study evaluated the antifungal activity of 4-chlorobenzyl p-coumarate, an unprecedented semi-synthetic molecule. Docking molecular and assay experiments were conducted to determine the Minimum Inhibitory Concentration (MIC) and Minimum Fungicidal Concentration (MFC), mode of action, effect on growth, fungal death kinetics, drug association, effects on biofilm, micromorphology, and against human keratinocytes. The investigation included 16 strains of Candida spp, including C. albicans, C. krusei, C. glabrata, C. tropicalis, C. dubliniensis, C. lusitaniae, C. utilis, C. rugosa, C. guilhermondi, and C. parapsilosis. Docking analysis predicted affinity between the molecule and all tested targets. MIC and MFC values ranged from 3.9 μg/mL (13.54 μM) to 62.5 μg/mL (217.01 μM), indicating a probable effect on the plasma membrane. The molecule inhibited growth from the first hour of testing. Association with nystatin proved to be indifferent. All concentrations of the molecule reduced fungal biofilm. The compound altered fungal micromorphology. The tested compound exhibited an IC50 of 7.90±0.40 μg/mL (27.45±1.42 μM) for keratinocytes. 4-chlorobenzyl p-coumarate showed strong fungicidal effects, likely through its action on the plasma membrane and alteration of fungal micromorphology, and mildly cytotoxic to human keratinocytes.

Virtualization and digital twins of the food supply chain for enhanced food safety

Meeting food safety requirements without jeopardizing quality attributes or sustainability involves adopting a holistic perspective of food products, their manufacturing processes and their storage and distribution practices. The virtualization of the food supply chain offers opportunities to evaluate, simulate, and predict challenges and mishaps potentially contributing to present and future food safety risks. Food systems virtualization poses several requirements: (1) a comprehensive framework composed of instrumental, digital, and computational methods to evaluate internal and external factors that impact food safety; (2) nondestructive and real-time sensing methods, such as spectroscopic-based techniques, to facilitate mapping and tracking food safety and quality indicators; (3) a dynamic platform supported by the Internet of Things (IoT) interconnectivity to integrate information, perform online data analysis and exchange information on product history, outbreaks, exposure to risky situations, etc.; and (4) comprehensive and complementary mathematical modeling techniques (including but not limited to chemical reactions and microbial inactivation and growth kinetics) based on extensive data sets to make realistic simulations and predictions possible. Despite current limitations in data integration and technical skills for virtualization to reach its full potential, its increasing adoption as an interactive and dynamic tool for food systems evaluation can improve resource utilization and rational design of products, processes and logistics for enhanced food safety. Virtualization offers affordable and reliable options to assist stakeholders in decision-making and personnel training. This chapter focuses on definitions and requirements for developing and applying virtual food systems, including digital twins, and their role and future trends in enhancing food safety.

Centroid of the bacterial growth curves: a metric to assess phage efficiency

Phage replication can be studied using various approaches, including measuring the optical density (OD) of a bacterial culture in a liquid medium in the presence of phages. A few quantitative methods are available to measure and compare the efficiency of phages by using a single index based on the analysis of OD curves. However, these methods are not always applicable to non-canonical OD curves. Using the concept of center of area (centroid), we developed a metric called Centroid Index (CI), sensitive to the trend of the growth curves (OD distribution) including bacterial regrowth, which is not considered by the methods already available. We also provide a user-friendly software to facilitate the calculation of CI. This method offers an alternative and more precise way to determine phage efficiency by considering the OD variations over time, which may help in the selection of phages for biocontrol applications.

Predictive modeling of molds effective elimination by external inactivation sources

Presented paper deals with a novel application of the (nonlinear) logistic equation to model an elimination of microscopic filaments types of fungi-molds from affected materials via different external inactivation techniques. It is shown that if the inactivation rate of the external source is greater than the maximum natural growth rate of mycelium, the mold colony becomes destroyed after a finite time. Otherwise, the mycelium may survive the external attack only at a sufficiently large initial concentration of the inoculum. Theoretically determined growth curves are compared with the experimental data for Aspergillus brasiliensis mold inactivated by using both cold atmospheric plasma (CAP) and UV-germicidal lamp. Model presented in the article may be applied also to other classes of microorganisms (e.g. bacteria).

Advancements in Predictive Microbiology: Integrating New Technologies for Efficient Food Safety Models

Predictive microbiology is a rapidly evolving field that has gained significant interest over the years due to its diverse application in food safety. Predictive models are widely used in food microbiology to estimate the growth of microorganisms in food products. These models represent the dynamic interactions between intrinsic and extrinsic food factors as mathematical equations and then apply these data to predict shelf life, spoilage, and microbial risk assessment. Due to their ability to predict the microbial risk, these tools are also integrated into hazard analysis critical control point (HACCP) protocols. However, like most new technologies, several limitations have been linked to their use. Predictive models have been found incapable of modeling the intricate microbial interactions in food colonized by different bacteria populations under dynamic environmental conditions. To address this issue, researchers are integrating several new technologies into predictive models to improve efficiency and accuracy. Increasingly, newer technologies such as whole genome sequencing (WGS), metagenomics, artificial intelligence, and machine learning are being rapidly adopted into newer-generation models. This has facilitated the development of devices based on robotics, the Internet of Things, and time-temperature indicators that are being incorporated into food processing both domestically and industrially globally. This study reviewed current research on predictive models, limitations, challenges, and newer technologies being integrated into developing more efficient models. Machine learning algorithms commonly employed in predictive modeling are discussed with emphasis on their application in research and industry and their advantages over traditional models.

Modeling the growth of Aspergillus brasiliensis affected by a nonthermal plasma

AIM

The main objective of the study was to develop and validate a model for the growth of Aspergillus brasiliensis on surfaces, specifically on agar culture medium. An additional aim was to determine conditions for complete growth inhibition of this micromycete using two different nonthermal plasma (NTP) sources.

METHODS AND RESULTS

The developed model uses two key parameters, namely the growth rate and growth delay, which depend on the cultivation temperature and the amount of inoculum. These parameters well describe the growth of A. brasiliensis and the effect of NTP on it. For complete fungus inactivation, a single 10-minute exposure to a diffuse coplanar surface barrier discharge was sufficient, while a point-to-ring corona discharge required several repeated 10-minute exposures at 24-h intervals.

CONCLUSIONS

The article presents a model for simulating the surface growth of A. brasiliensis and evaluates the effectiveness of two NTP sources in deactivating fungi on agar media.

Inferring fungal growth rates from optical density data

Quantifying fungal growth underpins our ability to effectively treat severe fungal infections. Current methods quantify fungal growth rates from time-course morphology-specific data, such as hyphal length data. However, automated large-scale collection of such data lies beyond the scope of most clinical microbiology laboratories. In this paper, we propose a mathematical model of fungal growth to estimate morphology-specific growth rates from easy-to-collect, but indirect, optical density (OD600) data of Aspergillus fumigatus growth (filamentous fungus). Our method accounts for OD600 being an indirect measure by explicitly including the relationship between the indirect OD600 measurements and the calibrating true fungal growth in the model. Therefore, the method does not require de novo generation of calibration data. Our model outperformed reference models at fitting to and predicting OD600 growth curves and overcame observed discrepancies between morphology-specific rates inferred from OD600 versus directly measured data in reference models that did not include calibration.

Repurposing the mammalian RNA-binding protein Musashi-1 as an allosteric translation repressor in bacteria

The RNA recognition motif (RRM) is the most common RNA-binding protein domain identified in nature. However, RRM-containing proteins are only prevalent in eukaryotic phyla, in which they play central regulatory roles. Here, we engineered an orthogonal post-transcriptional control system of gene expression in the bacterium Escherichia coli with the mammalian RNA-binding protein Musashi-1, which is a stem cell marker with neurodevelopmental role that contains two canonical RRMs. In the circuit, Musashi-1 is regulated transcriptionally and works as an allosteric translation repressor thanks to a specific interaction with the N-terminal coding region of a messenger RNA and its structural plasticity to respond to fatty acids. We fully characterized the genetic system at the population and single-cell levels showing a significant fold change in reporter expression, and the underlying molecular mechanism by assessing the in vitro binding kinetics and in vivo functionality of a series of RNA mutants. The dynamic response of the system was well recapitulated by a bottom-up mathematical model. Moreover, we applied the post-transcriptional mechanism engineered with Musashi-1 to specifically regulate a gene within an operon, implement combinatorial regulation, and reduce protein expression noise. This work illustrates how RRM-based regulation can be adapted to simple organisms, thereby adding a new regulatory layer in prokaryotes for translation control.

Turbidimetric flow analysis system for the investigation of microbial growth

The monitoring of life of microbial populations is of the uttermost importance in environmental and food analysis, agriculture, as well as in medicine. The duration of bacteria adaptation to new environmental conditions, its lifetime and the divisions' pace are the key information in many studies. It was found that the fully-mechanized flow analysis system based on solenoid valves and pumps, paired with a dedicated flow-through optoelectronic detector can be successfully applied for monitoring of bacteria growth. The applicability of the designed multicommutated flow analysis (MCFA) system was proved by analysis of solutions containing bacteria cells proceeded by tests of McFarland (McF) standards. The developed setup allowed modelling and simulation of microbial growth, as well as monitoring of the bacteria growth in real-time manner to be carried out. The monitor is useful for the quantitative estimation of the basic parameters of bacteria population like its size, the rate of bacteria multiplication, as well as the times of lag, log and stationary phases of microbial growth.

Dual Regulatory Role of Penicillium oxalicum SL2 in Soil: Phosphorus Solubilization and Pb Stabilization

The mechanisms of the P. oxalicum SL2-mediated microbial community on phosphorus solubilization and Pb stabilization were investigated through a 90-day soil experiment. In the treatments inoculated with P. oxalicum SL2, the amount of P. oxalicum SL2-GFP remained at 77.8%-138.6% of the initial inoculation amount after 90 days, and the available phosphorus (AP) content increased 21.7%-40.8% while EDTA-Pb decreased 29.9%-43.2% compared with CK treatment. SEM-EDS results showed that P. oxalicum SL2 changed the agglomeration degree of microaggregates and promoted the combination of Pb with C and O elements. These phenomena were enhanced when applied with Ca3(PO4)2. Microbial community analysis showed that P. oxalicum SL2 improved soil microbial activity, in which the fungi absolute abundance increased about 15 times within 90 days. Correlation analyses and a partial least-squares path model showed that the activation of Penicillium, Ascobolus, Humicola, and Spizellomyces in a fungal community increased the content of oxalate and AP, which directly decreased EDTA-Pb content, while the change of Bacillus, Ramlibacter, Gemmatimonas, and Candidatus Solibacter in the bacterial community regulated Fe/Mn/S/N cycle-related functions, thus promoting the conversion of Pb to oxidizable state. Our findings highlight that P. oxalicum SL2 enhanced the microbial-induced phosphate precipitation process by activating soil microbial communities and regulating their ecological functions.

Antibody preparation and age-dependent distribution of TLR8 in Bactrian camel spleens

BACKGROUND

Toll-like receptor 8 (TLR8) can recognize specific pathogen-associated molecular patterns and exert multiple immunological functions through activation of signaling cascades. However, the precise distribution and age-related alterations of TLR8 in the spleens of Bactrian camels have not yet been investigated. This study aimed to prepare a rabbit anti-Bactrian camel TLR8 polyclonal antibody and elucidate the distribution of TLR8 in the spleens of Bactrian camels at different age groups. The methodology involved the construction of the pET-28a-TLR8 recombinant plasmid, followed by the expression of TLR8 recombinant protein via prokaryotic expression. Subsequently, rabbits were immunized with the purified protein to prepare the TLR8 polyclonal antibody. Finally, twelve Alashan Bactrian camels were categorized into four groups: young (1-2 years), pubertal (3-5 years), middle-aged (6-16 years) and old (17-20 years). These camels received intravenous sodium pentobarbital (20 mg/kg) anesthesia and were exsanguinated to collect spleen samples. Immunohistochemical techniques were employed to observe and analyze the distribution patterns and age-related changes of TLR8 in the spleen.

RESULTS

The results showed that the TLR8 recombinant protein was expressed in the form of inclusion body with a molecular weight of 52 kDa, and the optimal induction condition involved 0.3 mmol/L IPTG induction for 8 h. The prepared antibody yielded a titer of 1:32 000, and the antibody demonstrated specific binding to TLR8 recombinant protein. TLR8 positive cells exhibited a consistent distribution pattern in the spleen across different age groups of Bactrian camels, primarily scattered within the periarterial lymphatic sheath of the white pulp, marginal zone, and red pulp. The predominant cell type expressing TLR8 was macrophages, with expression also observed in neutrophils and dendritic cells. Statistical analysis revealed that there were significant differences in the distribution density of TLR8 positive cells among different spleen regions at the same age, with the red pulp, marginal zone, and white pulp showing a descending order (P<0.05). Age-related changes indicated that the distribution density in the marginal zone and red pulp exhibited a similar trend of initially increasing and subsequently decreasing from young to old camels. As camels age, there was a significant decrease in the distribution density across all spleen regions (P<0.05).

CONCLUSIONS

The results confirmed that this study successfully prepared a rabbit anti-Bactrian camel TLR8 polyclonal antibody with good specificity. TLR8 positive cells were predominantly located in the red pulp and marginal zone of the spleen, signifying their pivotal role in the innate immune response of the spleen. Aging was found to significantly reduce the density of TLR8 positive cells, while leaving their scattered distribution characteristics unaffected. These findings provide valuable support for further investigations into the immunomorphology and immunosenescence of the spleen in Bactrian camels.

Derivative of 7-hydroxycoumarin has antifungal potential against Candida species and low cytotoxicity against human cells: In silico studies and biological evaluation

This study investigates the antifungal and cytotoxic properties of 7-(pentyloxy)-2H-chromen-2-one. Through molecular docking and dynamics simulations, we explored the compound's interactions with fungal cell protein targets. Notably, it exhibited strong affinities for 1,3β-glucan synthase, squalene epoxidase, δ-14-sterol reductase, 14-α-demethylase, and thymidylate synthase, with binding energies ranging from -100.39 to -73.15 kcal/mol. Molecular dynamics simulations confirmed its stable binding at active targets. The MIC and MFC values ranged from 67.16 μM (15.6 μg/mL) to 537.28 μM (125.0 μg/mL). The compound displayed promising antifungal effects, inhibiting fungal growth for at least 24 hours. Fungal plasma membrane function alteration likely contributed to these antifungal mechanisms. Additionally, the combination of the compound with nystatin, fluconazole, and caspofungin showed indifferent effects on antifungal activity. Cytotoxicity assessment in human keratinocyte cells (HaCaT) revealed an IC50 of 100 μM, which was approximately 1.5 times higher than the MIC for C. krusei. Thus, the compound exhibited strongly in silico and in vitro antifungal activity with low cytotoxicity in HaCaT cells. These findings support its potential as a candidate for further development as an antifungal compound.

Multi-faceted analysis of bacterial transformation of nitrofurantoin

Excessive presence of antibiotics and their residues can be dangerous to the natural environment. To reduce this negative effect, efficient strategies to remove them from the ecosystem are required. This study aimed to explore the potential of bacterial strains to degrade nitrofurantoin (NFT). Single strains isolated from contaminated areas, namely Stenotrophomonas acidaminiphila N0B, Pseudomonas indoloxydans WB, and Serratia marcescens ODW152 were employed in this study. Degradation efficiency and dynamic changes within the cells during NFT biodegradation were investigated. For this purpose, atomic force microscopy, flow cytometry, zeta potential, and particle size distribution measurements were applied. Serratia marcescens ODW152 showed the highest performance in removal of NFT (96 % in 28 days). The AFM images revealed modifications of cell shape and surface structure induced by NFT. Zeta potential showed significant variations during biodegradation. Cultures exposed to NFT had a broader size distribution than the control cultures due to increased cells agglomeration or aggregation. 1-Aminohydantoin and semicarbazide were detected as nitrofurantoin biotransformation products. They showed increased cytotoxicity toward bacteria as determined by spectroscopy and flow cytometry. Results of this study suggest that nitrofurantoin biodegradation leads to formation of stable transformation products that significantly affect the physiology and structure of bacterial cells.

Solution, exchangeable and fixed ammonium in natural diatomite as a simulated PRB material: effects of adsorption and bioregeneration processes

Ammonia nitrogen (NH₄⁺-N) is widely found in aquifers with strong reducibility or poor adsorptivity as a dissolved inorganic nitrogen pollutant. The application of adsorbents with effective long-term in situ bioregeneration as permeable reactive barrier (PRB) media for nitrogen removal has raised concern. In this study, the advantage of natural diatomite as a PRB material was investigated by exploring its NH₄⁺-N adsorption and desorption characteristics, and the ability of diatomite and zeolite to be loaded nitrifying bacteria was also compared. The results showed that the exchangeable ammonium from chemical-monolayer adsorption was the main form of NH₄⁺-N and was adsorbed by diatomite. Moreover, the adsorption process was limited with a maximum adsorption capacity of 0.677 mg g^-1. However, diatomite demonstrated an excellent loading of aerobic-heterotrophic microorganisms, even stronger than zeolite. Compared with zeolite reactors, a higher OD₆₀₀ value of nitrifiers, a faster NH₄⁺-N degradation rate and more abundant functional genes were observed during the bioregeneration process of diatomite. Both the solution and exchangeable ammonium forms were bioavailable, and the regeneration of diatomite was more than 80.0% after two days. Moreover, desorption-biodegradation was systematically analysed to determine the bioregeneration mechanism of diatomite. Diatomite with good regeneration ability can be used as a competitive alternative to address sudden nitrogen pollution.

Determination of Growth Rate and Virulence Plasmid Copy Number During Yersinia pseudotuberculosis Infection Using Droplet Digital PCR

Pathogenic bacteria have evolved the ability to evade their host defenses and cause diseases. Virulence factors encompass a wide range of adaptations that allow pathogens to survive and proliferate in the hostile host environment during successful infection. In human pathogenic Yersinia species, the potent type III secretion system (T3SS) and other essential virulence factors are encoded on a virulence plasmid. Here, we investigated the bacterial growth rate and plasmid copy number following a Yersinia infection using droplet digital PCR (ddPCR). ddPCR is an exceptionally sensitive, highly precise, and cost-efficient method. It enables precise quantification even from very small amounts of target DNA. This method also enables analysis of complex samples with large amounts of interfering DNA, such as infected tissues or microbiome studies.

Cytobacillus pseudoceanisediminis sp. nov., A Novel Facultative Methylotrophic Bacterium with High Heavy Metal Resistance Isolated from the Deep Underground Saline Spring

In this study, we present the characterization of the BNO1^T bacterial strain isolated from the deep subsurface saline spring at the Baksan Neutrino Observatory INR RAS (Kabardino-Balkaria, Russia). The complete genome sequence of the strain BNO1^T is 5,347,902 bp, with a GC content 41 and 49%. The cell wall peptidoglycan contains meso-diaminopimelic acid. The major isoprenoid quinone is MK-7 and the polar lipids are diphosphatidylglycerol, phosphatidylglycerol, and phosphatidylethanolamine. The major fatty acids are anteiso-C_15:0 (23.34%), iso-C_15:0 (20.10%), C_16:0 (11.96%), iso-C_16:0 (10.88%), and anteiso-C_17:0 (10.79%). The 16S rRNA gene sequence clearly demarcated the strain as belonging to Cytobacillus genera. Based on the phylogenetic analysis, ANI (average nucleotide identity) and dDDH (digital DNA-DNA hybridization) assessments we propose to assign the strain BNO1^T and other related strains to new species and to name it Cytobacillus pseudoceanisediminis sp. nov. (The values of ANI and dDDH between BNO1^T and Cytobacillus oceanisediminis CGMCC 1.10115 ^T are 80.65% and 24.7%, respectively; values of ANI and dDDH between BNO1^T and Cytobacillus firmus NCTC 10335 ^T are 89% and 38%, respectively). Genomic analysis of strain BNO1^T revealed pathways for C1 compounds oxidation and two pathways for C1 compounds assimilation: serine and ribulose monophosphate pathways. In addition, strain BNO1^T contains a plasmid (342,541 bp) coding multiple genes involved in heavy metal ion balance. Moreover, heavy metal toxicity testing confirmed the high potential of the strain BNO1^T as a source of metal resistance genes and enzymes. The type strain is BNO1^T (= BIM B-1921 ^T = VKM B-3664 ^T).

Density-dependent effects are the main determinants of variation in growth dynamics between closely related bacterial strains

Although closely related, bacterial strains from the same species show significant diversity in their growth and death dynamics. Yet, our understanding of the relationship between the kinetic parameters that dictate these dynamics is still lacking. Here, we measured the growth and death dynamics of 11 strains of Escherichia coli originating from different hosts and show that the growth patterns are clustered into three major classes with typical growth rates, maximal fold change, and death rates. To infer the underlying phenotypic parameters that govern the dynamics, we developed a phenomenological mathematical model that accounts not only for growth rate and its dependence on resource availability, but also for death rates and density-dependent growth inhibition. We show that density-dependent growth is essential for capturing the variability in growth dynamics between the strains. Indeed, the main parameter determining the dynamics is the typical density at which they slow down their growth, rather than the maximal growth rate or death rate. Moreover, we show that the phenotypic landscape resides within a two-dimensional plane spanned by resource utilization efficiency, death rate, and density-dependent growth inhibition. In this phenotypic plane, we identify three clusters that correspond to the growth pattern classes. Overall, our results reveal the tradeoffs between growth parameters that constrain bacterial adaptation.

Colonization of Penicillium oxalicum SL2 in Pb-contaminated paddy soil and its immobilization effect on soil Pb

Penicillium oxalicum SL2 (SL2) is a previously screened Pb-tolerant fungus that can promote crops growth. The relationship between SL2 colonization and Pb immobilization was studied to provide a theoretical basis for microbial remediation of Pb-contaminated paddy soil. In this study, green fluorescent protein (GFP) labeled SL2 was inoculated into different Pb-contaminated paddy soils (S1-S6). The Pb extracted from the soil by HNO₃, EDTA and CaCl₂ were used to characterize the available Pb. The results showed that the colonization of SL2 was divided into lag phase (0-7 days), growth phase (7-30 days), and mortality phase (30-90 days). SL2 colonized well in sandy soils rich in clay and total phosphorus with initial pH of 4.5-7.0. In addition, SL2 increased soil pH and decreased soil Eh, which was beneficial to immobilize Pb. In different soils, the highest percentages of CaCl₂-Pb, EDTA-Pb, and HNO₃-Pb immobilized by SL2 were 34.34%-40.53%, 17.05%-20.11%, and 7.39%-15.62%, respectively. Pearson correlation analysis showed that the percentages of CaCl₂-Pb and EDTA-Pb immobilized by SL2 were significantly positively correlated with the number of SL2 during the growth phase. SL2 mainly immobilized Pb in the growth phase and a higher peak number of SL2 was beneficial to the immobilization of Pb.

Differential toxicity of potentially toxic elements to human gut microbes

Specific microorganisms in the human gut (i.e., gut microbes) provide mutually beneficial outcomes such as microbial balance by inhibiting the growth of pathogenic organisms, immune system modulation, fermentation of ingested products, and vitamin production. The intake of contaminants including potenially toxic elements (PTEs) can occur through food, air, water and some medicines. The gut microbes not only can be affected by environmental contaminants but they themselves can alter the speciation and bioavailability of these contaminants. This research work was designed to demonstrate the relationship between increasing level of selected PTEs including As, Cd, Pb and Hg on the growth of selected gut microbes. The toxicity of above mentioned PTEs to three gut bacteria (Lactobacillus rhamnosus, Lactobacillus acidophilus and Escherichia coli) was examined. While the toxicity of all the cationic PTEs including Cd, Pb and Hg towards gut bacteria decreased with increasing pH, the anionic As species exhibited an opposite effect. The order of toxicity was Hg > Cd > Pb > As(III)>As(V) for E. coli; and Hg > Cd > As(III)>Pb > As(V) for the two Lactobacillus sp. Arsenite (AsIII) showed higher toxicity than arsenate (AsV) to gut bacteria. While As is an anion, Cd, Pb and Hg are cations and hence their binding capacity to the bacterial cell wall varied based on the charge dependent functional groups. However, the toxic effects of PTEs for a bacteria are controlled by their speciation and bioavailability.

Investigating the Ability of Growth Models to Predict In Situ Vibrio spp. Abundances

Vibrio spp. have an important role in biogeochemical cycles; some species are disease agents for aquatic animals and/or humans. Predicting population dynamics of Vibrio spp. in natural environments is crucial to predicting how the future conditions will affect the dynamics of these bacteria. The majority of existing Vibrio spp. population growth models were developed in controlled environments, and their applicability to natural environments is unknown. We collected all available functional models from the literature, and distilled them into 28 variants using unified nomenclature. Next, we assessed their ability to predict Vibrio spp. abundance using two new and five already published longitudinal datasets on Vibrio abundance in four different habitat types. Results demonstrate that, while the models were able to predict Vibrio spp. abundance to an extent, the predictions were not reliable. Models often underperformed, especially in environments under significant anthropogenic influence such as aquaculture and urban coastal habitats. We discuss implications and limitations of our analysis, and suggest research priorities; in particular, we advocate for measuring and modeling organic matter.

Machine learning-assisted discovery of growth decision elements by relating bacterial population dynamics to environmental diversity

Microorganisms growing in their habitat constitute a complex system. How the individual constituents of the environment contribute to microbial growth remains largely unknown. The present study focused on the contribution of environmental constituents to population dynamics via a high-throughput assay and data-driven analysis of a wild-type Escherichia coli strain. A large dataset constituting a total of 12,828 bacterial growth curves with 966 medium combinations, which were composed of 44 pure chemical compounds, was acquired. Machine learning analysis of the big data relating the growth parameters to the medium combinations revealed that the decision-making components for bacterial growth were distinct among various growth phases, e.g., glucose, sulfate, and serine for maximum growth, growth rate, and growth delay, respectively. Further analyses and simulations indicated that branched-chain amino acids functioned as global coordinators for population dynamics, as well as a survival strategy of risk diversification to prevent the bacterial population from undergoing extinction.

Long-term microglial phase-specific dynamics during single vessel occlusion and recanalization

Vascular occlusion leading to brain dysfunctions is usually considered evoking microglia-induced inflammation response. However, it remains unclear how microglia interact with blood vessels in the development of vascular occlusion-related brain disorders. Here, we illuminate long-term spatiotemporal dynamics of microglia during single vessel occlusion and recanalization. Microglia display remarkable response characteristics in different phases, including acute reaction, rapid diffusion, transition and chronic effect. Fibrinogen-induced microglial cluster promotes major histocompatibility complex II (MHCII) expression. Microglial soma represents a unique filament-shape migration and has slower motility compared to the immediate reaction of processes to occlusion. We capture proliferative microglia redistribute territory. Microglial cluster resolves gradually and microglia recover to resting state both in the morphology and function in the chronic effect phase. Therefore, our study offers a comprehensive analysis of spatiotemporal dynamics of microglia and potential mechanisms to both vessel occlusion and recanalization. Microglial phase-specific response suggests the morphological feature-oriented phased intervention would be an attractive option for vascular occlusion-related diseases treatments.

The spatiotemporal dynamics of the microglial inflammatory response to single vessel occlusion and recanalization are analysed, revealing four different response phases.

Development of mixed starter culture for the fermentation of Ethiopian honey wine, Tej

Ethiopian honey wine is one of the country's most popular spontaneously fermented traditional alcoholic beverages. However, the final product of this natural fermentation system is frequently of poor and inconsistent quality. Furthermore, it makes the process difficult to predict, control, and correct. Thus, the main aim of this study was to develop a direct fermentation system for Ethiopian honey wine, Tej. After isolating fermentative microbial strains from Tej samples, they were subjected to intensive screening to fit to its purpose. Later, phenotypic and genotypic characterization, and inoculation of isolates to honey-must were performed sequentially. Finally, microbial interaction and physicochemical analysis, including volatile compounds profiling, were done for the inoculated samples. The identified isolates were strains of Saccharomycetaceae and Lactobacillaceae families. These strains showed a good ability to tolerate osmotic stress and a lower pH environment. Tej sample produced by mixed culture inoculation of Saccharomyces and Lactobacillus species showed similar physicochemical, volatile compounds, and sensory attributes values with that of the control sample. Thus, a mixture of Saccharomyces and Lactobacillus strains could be used as a starter culture to produce Ethiopian honey, Tej, without scarifying of its major quality attributes.

In vitro Susceptibility to β-Lactam Antibiotics and Viability of Neisseria gonorrhoeae Strains Producing Plasmid-Mediated Broad- and Extended-Spectrum β-Lactamases

Neisseria gonorrhoeae plasmids can mediate high-level antimicrobial resistance. The emergence of clinical isolates producing plasmid β-lactamases that can hydrolyze cephalosporins, the mainstay treatment for gonorrhea, may be a serious threat. In this work, N. gonorrhoeae strains producing plasmid-mediated broad- and extended-spectrum β-lactamases (ESBLs) were obtained in vitro, and their viability and β-lactam antibiotic susceptibility were studied. Artificial pbla_TEM-1 and pbla_TEM-20 plasmids were constructed by site-directed mutagenesis from a pbla_TEM-135 plasmid isolated from a clinical isolate. Minimum inhibitory concentration (MIC) values for a series of β-lactam antibiotics, including benzylpenicillin, ampicillin, cefuroxime, ceftriaxone, cefixime, cefotaxime, cefepime, meropenem, imipenem, and doripenem, were determined. The N. gonorrhoeae strain carrying the pbla_TEM-20 plasmid exhibited a high level of resistance to penicillins and second–fourth-generation cephalosporins (MIC ≥2 mg/L) but not to carbapenems (MIC ≤0.008 mg/L). However, this strain stopped growing after 6 h of culture. The reduction in viability was not associated with loss of the plasmid but can be explained by the presence of the plasmid itself, which requires additional reproduction costs, and to the expression of ESBLs, which can affect the structure of the peptidoglycan layer in the cell membrane. Cell growth was mathematically modeled using the generalized Verhulst equation, and the reduced viability of the plasmid-carrying strains compared to the non-plasmid-carrying strains was confirmed. The cell death kinetics of N. gonorrhoeae strains without the pbla_TEM-20 plasmid in the presence of ceftriaxone can be described by a modified Chick–Watson law. The corresponding kinetics of the N. gonorrhoeae strain carrying the pbla_TEM-20 plasmid reflected several processes: the hydrolysis of ceftriaxone by the TEM-20 β-lactamase and the growth and gradual death of cells. The demonstrated reduction in the viability of N. gonorrhoeae strains carrying the pbla_TEM-20 plasmid probably explains the absence of clinical isolates of ESBL-producing N. gonorrhoeae.

Advances in multi-omics based quantitative microbial risk assessment in the dairy sector: A semi-systematic review

With the increasing consumption of packaged and ready-to-eat food products, the risk of foodborne illness has drastically increased and so has the dire need for proper management. The conventional Microbial Risk Assessment (MRA) investigations require prior knowledge of process flow, exposure, and hazard assessment throughout the supply chain. These data are often generated using conventional microbiological approaches based either on shelf-life studies or specific spoilage organisms (SSOs), frequently overlooking crucial information such as antimicrobial resistance (AMR), biofilm formation, virulence factors and other physiological variations coupled with bio-chemical characteristics of food matrix. Additionally, the microbial risks in food are diverse and heterogenous, that might be an outcome of growth and activity of multiple microbial populations rather than a single species contamination. The uncertainty on the microbial source, time as well as point of entry into the food supply chain poses a constraint to the efficiency of preventive approaches and conventional MRA. In the last few decades, significant breakthroughs in molecular methods and continuously progressing bioinformatics tools have opened up a new horizon for risk analysis-based approaches in food safety. Real time polymerase chain reaction (qPCR) and kit-based assays provide better accuracy and precision with shorter processing time. Despite these improvements, the effect of complex food matrix on growth environment and recovery of pathogen is a persistent problem for risk assessors. The dairy industry is highly impacted by spoilage and pathogenic microorganisms. Therefore, this review discusses the evolution and recent advances in MRAmethodologies equipped with predictive interventions and "multi-omics" approach for robust MRA specifically targeting dairy products. It also highlights the limiting gap area and the opportunity for improvement in this field to ensure precision food safety.

Assessment of a potential bioproduct for controlling Cerotoma arcuata tingomariana (Coleoptera: Chrysomelidae)

AIMS

The leaf-feeding pest Cerotoma arcuata tingomariana (Bechyné) (Coleoptera: Chrysomelidae) produces huge economic losses in different crops. This study aimed to produce conidia by semisolid-state fermentation and to establish the insecticidal activity of two formulation prototypes based on a native Beauveria bassiana isolate for controlling this pest.

METHODS AND RESULTS

A novel fabric-based semisolid-state fermentation strategy for quick and large-scale conidia production was performed and characterized. Conidia were formulated as an emulsifiable concentrate (EC) and a water-dispersible granulate (WG). Afterwards, the mortality of C. a. tingomariana adults was assessed. A conidia concentration of 2.9 x10⁹ conidia cm^-2 was obtained after nine days-course fermentation and a yield of 33.4 g kg^-1 dry-substrate.

CONCLUSIONS

The polyester fabric-based fermentation is an efficient technique for producing and collecting B. bassiana spores. Regarding LC₉₀ , the potency analysis showed that the EC was 21-fold more potent than the non-formulated conidia, and ~2.6-fold more potent than the WG.

SIGNIFICANCE AND IMPACT OF STUDY

A high throughput fermentation based on polyester fabric as support for B. bassiana conidia production and subsequent formulation as an EC comprises a promising strategy for obtaining a bioproduct to control adults of C. a. tingomariana and other Chrysomelidae pests.

PM10 and Other Climatic Variables Are Important Predictors of Seasonal Variability of Coccidioidomycosis in Arizona

Coccidioidomycosis (Valley fever) is a disease caused by the fungal pathogens Coccidioides immitis and Coccidioides posadasii that are endemic to the southwestern United States and parts of Mexico and South America. Throughout the range where the pathogens are endemic, there are seasonal patterns of infection rates that are associated with certain climatic variables. Previous studies that looked at annual and monthly relationships of coccidioidomycosis and climate suggest that infection numbers are linked with precipitation and temperature fluctuations; however, these analytic methods may miss important nonlinear, nonmonotonic seasonal relationships between the response (Valley fever cases) and explanatory variables (climate) influencing disease outbreaks. To improve our current knowledge and to retest relationships, we used case data from three counties of high endemicity in southern Arizona paired with climate data to construct a generalized additive statistical model that explores which meteorological parameters are most useful in predicting Valley fever incidence throughout the year. We then use our model to forecast the pattern of Valley fever cases by month. Our model shows that maximum monthly temperature, average PM10, and total precipitation 1 month prior to reported cases (lagged model) were all significant in predicting Valley fever cases. Our model fits Valley fever case data in the region of endemicity of southern Arizona and captures the seasonal relationships that predict when the public is at higher risk of being infected. This study builds on and retests relationships described by previous studies regarding climate variables that are important for predicting risk of infection and understanding this fungal pathogen. IMPORTANCE The inhalation of environmental infectious propagules from the fungal pathogens Coccidioides immitis and Coccidioides posadasii by susceptible mammals can result in coccidioidomycosis (Valley fever). Arizona is known to be a region where the pathogen is hyperendemic, and reported cases are increasing throughout the western United States. Coccidioides spp. are naturally occurring fungi in arid soils. Little is known about ecological factors that influence the growth of these fungi, and a higher environmental burden may result in increases in human exposure and therefore case rates. By examining case and climate data from Arizona and using generalized additive statistical models, we were able to examine the relationship between disease outbreaks and climatic variables and predict seasonal time points of increased infection risk.

Reparameterization of the Weibull model for practical uses in food science

The reparameterization of the Weibull cumulative distribution function and its survival function was performed to obtain meaningful parameters in food and biological sciences such as the lag phase (λ), the maximum rate ( μ max ${\mu _{{\rm{max}}}}$ ), and the maximum increase/decrease of the function (A). The application of the Lambert function was crucial in order to achieve an explicit mathematical solution. Since the reparameterized model is applicable only when the shape parameter (α) is greater than one, the Weibull model was modified with the introduction of a new parameter ( μ β ${\mu _\beta }$ ) that represents the model rate at time β (scale parameter). All models were applied to literature data on food technology and microbiology topics: Microbial growth, thermal microbial inactivation, thermal degradation kinetics, and particle size distributions. The Weibull model and the reparameterized versions showed identical fitting performance in terms of coefficient of determination, residual mean standard error, values of residuals, and estimated values of the parameters. Some faults in the datasets used in this study permitted to re-mark the criticality of a good experimental plan when data modeling is approached. The parameter μ β ${\mu _\beta }$ resulted in an interesting new rate parameter that is not correlated with the scale parameter ( | r ¯ | $| {\bar{r}} |$ = 0.64 ± 0.37) and highly correlated with the shape parameter ( | r ¯ | $| {\bar{r}} |$ = 0.90 ± 0.11). Also, the reparameterization of the Weibull probability density function was performed by using both the standard and new parameters and applied to experimental data and gave useful information from the distribution curve, such as the value of the mode ( μ max ${\mu _{{\rm{max}}}}$ ) and a measure of the curve skewness (λ).

Models of the water activity effect on microbial growth rate and initiation

The role water activity, a_w, plays in microbial growth by itself or in conjunction with other factors, notably temperature and pH, has been described mathematically by different algebraic models obtained by fitting experimental growth rate vs. a_w relationships. Many of these models have one, two, or all three cardinal parameters, namely the minimal, optimal, and maximal a_w, in their formulation. Although they all have good fit as judged by statistical criteria, their different mathematical structures have different ramifications concerning the threshold a_w for growth initiation, and the growth pattern around and beyond the optimal a_w level where it exists. The focus of this review is on the biological implications of the different growth rate vs. a_w models inferred exclusively from their mathematical properties, leaving out any statistical fit considerations. It also describes a recently proposed single-parameter model of monotonic or the monotonic part of experimental growth rate vs. a_w curves, which can be combined with a decay term to produce a general conceptual model of peaked and monotonic microbial growth rate vs. a_w relationships over the entire a_w range. KEY POINTS: • Traditional and new growth rate vs. a_w models are presented and their implications compared. • Analogy between a_w and the temperature or pH effect on microbial growth rate is reassessed. • Cardinal parameters alone do not establish a unique growth rate vs. a_w relationship.

Logistic modeling to predict the minimum inhibitory concentration (MIC) of olive leaf extract (OLE) against Listeria monocytogenes

Olive leaf extract (OLE) has been increasingly recognized as a natural and effective antimicrobial against a host of foodborne pathogens. This study attempts to predict the minimum inhibitory concentration (MIC) of OLE against Listeria monocytogenes F2365 by utilizing the asymptotic deceleration point (PDA) in a logistic model (LM), namely MIC-PDA. The experimental data obtained from the inhibitory rate (IR) versus OLE concentration against L. monocytogenes were sufficiently fitted (R2 = 0.88957). Five significant critical points were derived by taking the multi-order derivatives of the LM function: the inflection point (PI), the maximum acceleration point (PAM), the maximum deceleration point (PDM), the absolute acceleration point (PAA), and the asymptotic deceleration point (PDA). The PDA ([OLE] = 37.055 mg/mL) was employed to approximate the MIC-PDA. This MIC value was decreased by over 42% compared to the experimental MIC of 64.0 mg/mL, obtained using the conventional 2-fold dilution method (i.e., MIC-2fold). The accuracy of MIC-PDA was evaluated by an in vitro L. monocytogenes growth inhibition assay. Finally, the logistic modeling method was independently validated using our previously published inhibition data of OLE against the growths of Escherichia coli O157:H7 and Salmonella enteritidis. The MIC-PDA (for [OLE]) values were estimated to be 41.083 and 35.313 mg/mL, respectively, compared to the experimental value of 62.5 mg/mL. Taken together, MIC-PDA, as estimated from the logistic modeling, holds the potential to shorten the time and reduce cost when OLE is used as an antimicrobial in the food industry.

Isolation and Optimization of Culture Conditions of a Bioflocculant-Producing Fungi from Kombucha Tea SCOBY

Biolocculants are gaining attention in research due to their environmental friendliness and innocuousness to human in comparison to the conventional flocculants. The present study aimed to investigate the ability of fungi from Kombucha tea SCOBY to produce effective bioflocculant in bulk. A 16S rRNA gene sequence analysis was utilized to identify the isolate. The medium composition (carbon and nitrogen sources) and culture conditions (inoculum size, temperature, shaking speed, pH, and time) were optimized using one-factor-at-a-time method. The functional groups, morphology, and crystallinity of the bioflocculant were evaluated using Fourier transform infrared (FT-IR), scan electron microscope (SEM) and X-ray diffractometry (XRD). The fungus was found to be Pichia kudriavzevii MH545928.1. It produced a bioflocculant with flocculating activity of 99.1% under optimum conditions; 1% (v/v) inoculum size, glucose and peptone as nutrient sources, 35 °C, pH 7 and the shaking speed of 140 rpm for 60 h. A cumulus-like structure was revealed by SEM; FT-IR displayed the presence of hydroxyl, carboxyl, amine, and thiocynates. The XRD analysis demonstrated the bioflocculant to have big particles with diffraction peaks at 10° and 40° indicating its crystallinity. Based on the obtained results, P. kudriavzevii MH545928.1 has potential industrial applicability as a bioflocculant producer.

Decomposition of Growth Curves into Growth Rate and Acceleration: a Novel Procedure to Monitor Bacterial Growth and the Time-Dependent Effect of Antimicrobials

In this paper, a simple numerical procedure is presented to monitor the growth of Streptococcus sanguinis over time in the absence and presence of propolis, a natural antimicrobial. In particular, it is shown that the real-time decomposition of growth curves obtained through optical density measurements into growth rate and acceleration can be a powerful tool to precisely assess a large range of key parameters [i.e. lag time (t₀), starting growth rate (γ₀), initial acceleration of the growth (a₀), maximum growth rate (γ_max), maximum acceleration (a_max) and deceleration (a_min) of the growth and the total number of cells at the beginning of the saturation phase (N_s)] that can be readily used to fully describe growth over time. Consequently, the procedure presented provides precise data of the time course of the different growth phases and features, which is expected to be relevant, for instance, to thoroughly evaluate the effect of new antimicrobial agents. It further provides insight into predictive microbiology, likely having important implications to assumptions adopted in mathematical models to predict the progress of bacterial growth. Importance: The new and simple numerical procedure presented in this paper to analyze bacterial growth will possibly allow identifying true differences in efficacy among antimicrobial drugs for their applications in human health, food security, and environment, among others. It further provides insight into predictive microbiology, likely helping in the development of proper mathematical models to predict the course of bacterial growth under diverse circumstances.

The Persistence of Staphylococcus aureus in Pressure Ulcers: A Colonising Role

Decubitus pressure ulcers (PU) are a major complication of immobilised patients. Staphylococcus aureus is one of the most frequently detected microorganisms in PU samples; however, its persistence and role in the evolution of these wounds is unknown. In this study, we analysed S. aureus strains isolated from PU biopsies at inclusion and day 28. Eleven S. aureus (21.1%) were detected in 52 patients at inclusion. Only six PUs (11.5%) continued to harbour this bacterium at day 28. Using a whole genome sequencing approach (Miseq®, Illumina), we confirmed that these six S. aureus samples isolated at D28 were the same strain as that isolated at inclusion, with less than 83 bp difference. Phenotypical studies evaluating the growth profiles (Infinite M Mano, Tecan®) and biofilm formation (Biofilm Ring Test®) did not detect any significant difference in the fitness of the pairs of S. aureus. However, using the Caenorhabditis elegans killing assay, a clear decrease of virulence was observed between strains isolated at D28 compared with those isolated at inclusion, regardless of the clinical evolution of the PU. Moreover, all strains at inclusion were less virulent than a control S. aureus strain, i.e., NSA739. An analysis of polymicrobial communities of PU (by metabarcoding approach), in which S. aureus persisted, demonstrated no impact of Staphylococcus genus on PU evolution. Our study suggested that S. aureus presented a colonising profile on PU with no influence on wound evolution.

Mathematical Modeling of Total Volatile Basic Nitrogen and Microbial Biomass in Stored Rohu (Labeo rohita) Fish

The paper deals with the dynamical behavior of fish volatiles and microbial growth in stored Rohu fish through mathematical modeling. Total volatile basic nitrogen (TVB-N) is formed in stored Rohu (Labeo rohita) fish due to some complicated biochemical activities. It considered the biomass populace of volatiles (TVB-N) and microorganisms in fish stored at two different temperatures, separately. The different models may be used to forecast TVB-N, microbial populace (total viable count; TVC), and various properties change during nourishment stockpiling coordination and diverse preparing tasks. Models might be dynamic, exact, hypothetical, and stochastic in nature. Various parameters are required to build up a model which can be utilized to foresee the freshness and timeframe of realistic usability of storage duration. The ecosystem is represented by algebraic equations involving volatile compounds and microbial populations separately. TVB-N and TVC of stored rohu fish was determined at an interval of 4 days for 24 days. The initial and final biomass of TVB-N was 4.57 (fresh sample), 19.88 (24 days at 5°C), and 7.10 mg/100 g (24th day at 0°C), respectively. The TVC values were found to be 2.29 (fresh sample), 9.5 (24 days at 5°C) and 8.1 log (cfu/g) (24 days at 0°C). Exponential, modified exponential, Howgate, and adapted Howgate models were considered for modeling the TVB-N formation, whereas logistic, modified logistic, Gompertz, and modified Gompertz model were taken forward for modeling the microbial biomass developed in stored rohu fish. The exponential model found be the best fit model fit model for TVB-N prediction in rohu fish stored at 0 and 5°C as it showed the highest R2 (0.9796, 0.9887) the lowest χ2 (0.2782, 0.3976), RMSE (0.52741, 0.6306) AIC (−7.3122, −4.8106), AICc (−0.5122, 1.9894) and BIC (−7.4204, −4.9188), respectively. The Gompertz model was found to be the best fit model for microbial biomass prediction in rohu fish stored at 5°C (R2 = 0.9947, χ2 = 0.0537, AIC = −18.379, AICc = −6.3792 and BIC = −18.542), in contrast, both of the logistic and modified logistic models were the best suited at 0°C storage condition (R2 = 0.9919, χ2 = 0.0823).

Bacterial growth dynamics and pharmacokinetic-pharmacodynamic relationships of rifampicin and bedaquiline in BALB/c mice

BACKGROUND AND PURPOSE

Translational efforts in the evaluation of novel anti-tubercular drugs demand better integration of pharmacokinetic-pharmacodynamic data arising from preclinical protocols. However, parametric approaches that discriminate drug effect from the underlying bacterial growth dynamics have not been fully explored, making it difficult to translate and/or extrapolate preclinical findings to humans. This analysis aims to develop a drug-disease model that allows distinction between drug- and system-specific properties.

EXPERIMENTAL APPROACH

Given their clinical relevance, rifampicin and bedaquiline were used as test compounds. A two-state model was used to describe bacterial growth dynamics. The approach assumes the existence of fast- and slow-growing bacterial populations. Drug effect on the growth dynamics of each subpopulation was characterised in terms of potency (EC₅₀ -F and EC₅₀ -S) and maximum killing rate.

KEY RESULTS

The doubling time of the fast- and slow-growing population was estimated to be 25 h and 42 days, respectively. Rifampicin was more potent against the fast-growing (EC₅₀ -F = 4.8 mg·L^-1 ), as compared with the slow-growing population (EC₅₀ -S = 60.2 mg·L^-1 ). Bedaquiline showed higher potency than rifampicin (EC₅₀ -F = 0.19 mg·L^-1 ; EC₅₀ -S = 3.04 mg·L^-1 ). External validation procedures revealed an effect of infection route on the apparent potency of rifampicin.

CONCLUSION AND IMPLICATIONS

Model parameter estimates suggest that nearly maximum killing rate is achieved against fast-growing, but not against slow-growing populations at the tested doses. Evidence of differences in drug potency for each subpopulation may facilitate the translation of preclinical findings and improve the dose rationale for anti-tubercular drugs in humans.

Engineering modeling frameworks for microbial food safety at various scales

The landscape of mathematical model-based understanding of microbial food safety is wide and deep, covering interdisciplinary fields of food science, microbiology, physics, and engineering. With rapidly growing interest in such model-based approaches that increasingly include more fundamental mechanisms of microbial processes, there is a need to build a general framework that steers this evolutionary process by synthesizing literature spread over many disciplines. The framework proposed here shows four interconnected, complementary levels of microbial food processes covering sub-cellular scale, microbial population scale, food scale, and human population scale (risk). A continuum of completely mechanistic to completely empirical models, widely-used and emerging, are integrated into the framework; well-known predictive microbiology modeling being a part of this spectrum. The framework emphasizes fundamentals-based approaches that should get enriched over time, such as the basic building blocks of microbial population scale processes (attachment, migration, growth, death/inactivation and communication) and of food processes (e.g., heat and moisture transfer). A spectrum of models are included, for example, microbial population modeling covers traditional predictive microbiology models to individual-based models and cellular automata. The models are shown in sufficient quantitative detail to make obvious their coupling, or their integration over various levels. Guidelines to combine sub-processes over various spatial and time scales into a complete interdisciplinary and multiphysics model (i.e., a system) are provided, covering microbial growth/inactivation/transport and physical processes such as fluid flow and heat transfer. As food safety becomes increasingly predictive at various scales, this synthesis should provide its roadmap. This big picture and framework should be futuristic in driving novel research and educational approaches.

Bioanalytical insight into the life of microbial populations: A chemical monitoring of ureolytic bacteria growth

In this publication an alternative approach to investigations of bacterial growth is proposed. Contrary to the conventional physical methods it is based on enzyme activity detection. The procedure for real-time and on-line monitoring of microbial ureolytic activity (applied as a model experimental biosystem) in the flow analysis format is presented. The developed fully-mechanized bioanalytical flow system is composed of solenoid micropumps and microvalves actuated by Arduino microcontroller. The photometric detection based on Nessler reaction is performed using dedicated flow-through optoelectronic detector made of paired light emitting diodes. The developed bioanalytical system allows discrete assaying of microbial urease in the wide range of activity up to 5.4 U mL^-1 with detection limit below 0.44 U mL^-1, a high sensitivity in the linear range of response (up to 200 mV U^-1 mL and relatively high throughput (9 detection per hour). The proposed differential procedure of measurements (i.e. a difference between peaks register for sample with and without external addition of urea is treated as an analytical signal) allows elimination of interfering effects from substrate and products of biocatalysed reaction as well as other components of medium used for microbial growth. The developed bioanalytical system was successfully applied for the control of growth of urease-positive bacteria strains (Proteus vulgaris, Klebsiella pneumoniae and Paracoccus yeei) including examination of effects from various microbial cultivation conditions like temperature, composition of culture medium and amount of substrate required for induction of bacterial enzymatic activity. The developed bioanalytical flow system can be applied for metabolic activity-based estimation of parameters of lag and log phases of microbial growth as well as for detection of decline phase.