Acinetobacter baumannii Genomic Sequence-Based Core Genome Multilocus Sequence Typing Using Ridom SeqSphere+ and Antimicrobial Susceptibility Prediction in ARESdb.

Whole-genome sequencing (WGS) is rapidly replacing traditional typing methods for the investigation of infectious disease outbreaks. Additionally, WGS data are being used to predict phenotypic antimicrobial susceptibility. Acinetobacter baumannii, which is often multidrug-resistant, is a significant culprit in outbreaks in health care settings. A well-characterized collection of A. baumannii was studied using core genome multilocus sequence typing (cgMLST). Seventy-two isolates previously typed by PCR-electrospray ionization mass spectrometry (PCR/ESI-MS) provided by the Antimicrobial Resistance Leadership Group (ARLG) were analyzed using a clinical microbiology laboratory developed workflow for cgMLST with genomic susceptibility prediction performed using the ARESdb platform. Previously performed PCR/ESI-MS correlated with cgMLST using relatedness thresholds of allelic differences of ≤9 and ≤200 allelic differences in 78 and 94% of isolates, respectively. Categorical agreement between genotypic and phenotypic antimicrobial susceptibility across a panel of 11 commonly used drugs was 89%, with minor, major, and very major error rates of 8%, 11%, and 1%, respectively.

Modifiable Risk Factors for the Emergence of Ceftolozane-tazobactam Resistance.

BACKGROUND: Ceftolozane-tazobactam (TOL-TAZ) affords broad coverage against Pseudomonas aeruginosa. Regrettably, TOL-TAZ resistance has been reported. We sought to identify modifiable risk factors that may reduce the emergence of TOL-TAZ resistance. METHODS: Twenty-eight consecutive patients infected with carbapenem-resistant P. aeruginosa isolates susceptible to TOL-TAZ, treated with ≥72 hours of TOL-TAZ , and with P. aeruginosa isolates available both before and after TOL-TAZ exposure between January 2018 and December 2019 in Baltimore, Maryland, were included. Cases were defined as patients with at least a 4-fold increase in P. aeruginosa TOL-TAZ MICs after exposure to TOL-TAZ. Independent risk factors for the emergence of TOL-TAZ resistance comparing cases and controls were investigated using logistic regression. Whole genome sequencing of paired isolates was used to identify mechanisms of resistance that emerged during TOL-TAZ therapy. RESULTS: Fourteen patients (50%) had P. aeruginosa isolates which developed at least a 4-fold increase in TOL-TAZ MICs(ie, cases). Cases were more likely to have inadequate source control (29% vs 0%, P = .04) and were less likely to receive TOL-TAZ as an extended 3-hour infusion (0% vs 29%; P = .04). Eighty-six percent of index isolates susceptible to ceftazidime-avibactam (CAZ-AVI) had subsequent P. aeruginosa isolates with high-level resistance to CAZ-AVI, after TOL-TAZ exposure and without any CAZ-AVI exposure. Common mutations identified in TOL-TAZ resistant isolates involved AmpC, a known binding site for both ceftolozane and ceftazidime, and DNA polymerase. CONCLUSIONS: Due to our small sample size, our results remain exploratory but forewarn of the potential emergence of TOL-TAZ resistance during therapy and suggest extending TOL-TAZ infusions may be protective. Larger studies are needed to investigate this association.

Core Genome Multilocus Sequence Typing and Prediction of Antimicrobial Susceptibility Using Whole-Genome Sequences of Escherichia coli Bloodstream Infection Isolates.

In total, 50 Escherichia coli bloodstream isolates from the clinical laboratory and 12 E. coli isolates referred for pulsed-field gel electrophoresis (PFGE) were sequenced, assessed for clonality using core genome multilocus sequence typing (cgMLST), and evaluated for genomic susceptibility predictions using ARESdb. Results of sequence typing using whole-genome sequencing (WGS)-based MLST and sequence type (ST)-specific PCR were identical. Overall categorical agreement between genotypic (ARESdb) and phenotypic susceptibility testing for 62 isolates and 11 antimicrobial agents was 91%. Among the referred isolates, high major error rates were found for ceftazidime, cefepime, and piperacillin-tazobactam.

Multicenter Evaluation of the Unyvero Platform for Testing Bronchoalveolar Lavage Fluid.

Bronchoalveolar lavage (BAL) culture is a standard, though time-consuming, approach for identifying microorganisms in patients with severe lower respiratory tract (LRT) infections. The sensitivity of BAL culture is relatively low, and prior antimicrobial therapy decreases the sensitivity further, leading to overuse of empirical antibiotics. The Unyvero LRT BAL Application (Curetis GmbH, Germany) is a multiplex molecular panel that detects 19 bacteria, 10 antibiotic resistance markers, and a fungus, Pneumocystis jirovecii, in BAL fluid in ∼4.5 h. Its performance was evaluated using 1,016 prospectively collected and 392 archived specimens from 11 clinical trial sites in the United States. Overall positive and negative percent agreements with culture results for identification of bacteria that grow in routine cultures were 93.4% and 98.3%, respectively, with additional potential pathogens identified by Unyvero in 21.7% of prospectively collected specimens. For detection of P. jirovecii, the positive percent agreement with standard testing was 87.5%. Antibiotic resistance marker results were compared to standard antibiotic susceptibility test results to determine positive predictive values (PPVs). PPVs ranged from 80 to 100%, based on the microorganism and specific resistance marker(s). The Unyvero LRT BAL Application provides accurate detection of common agents of bacterial pneumonia and of P. jirovecii The sensitivity and rapidity of this panel suggest significant clinical value for choosing appropriate antibiotics and for antibiotic stewardship.

Assessing the heterogeneity of in silico plasmid predictions based on whole-genome-sequenced clinical isolates.

High-throughput next-generation shotgun sequencing of pathogenic bacteria is growing in clinical relevance, especially for chromosomal DNA-based taxonomic identification and for antibiotic resistance prediction. Genetic exchange is facilitated for extrachromosomal DNA, e.g. plasmid-borne antibiotic resistance genes. Consequently, accurate identification of plasmids from whole-genome sequencing (WGS) data remains one of the major challenges for sequencing-based precision medicine in infectious diseases. Here, we assess the heterogeneity of four state-of-the-art tools (cBar, PlasmidFinder, plasmidSPAdes and Recycler) for the in silico prediction of plasmid-derived sequences from WGS data. Heterogeneity, sensitivity and precision were evaluated by reference-independent and reference-dependent benchmarking using 846 Gram-negative clinical isolates. Interestingly, the majority of predicted sequences were tool-specific, resulting in a pronounced heterogeneity across tools for the reference-independent assessment. In the reference-dependent assessment, sensitivity and precision values were found to substantially vary between tools and across taxa, with cBar exhibiting the highest median sensitivity (87.45%) but a low median precision (27.05%). Furthermore, integrating the individual tools into an ensemble approach showed increased sensitivity (95.55%) while reducing the precision (25.62%). CBar and plasmidSPAdes exhibited the strongest concordance with respect to identified antibiotic resistance factors. Moreover, false-positive plasmid predictions typically contained only few antibiotic resistance factors. In conclusion, while high degrees of heterogeneity and variation in sensitivity and precision were observed across the different tools and taxa, existing tools are valuable for investigating the plasmid-borne resistome. Nevertheless, additional studies on representative clinical data sets will be necessary to translate in silico plasmid prediction approaches from research to clinical application.

A high leukocyte count and administration of hydrocortisone hamper PCR-based diagnostics for bloodstream infections.

Bloodstream infections (BSIs) require an accurate and fast identification of causative pathogens. Molecular diagnostics, in particular polymerase chain reaction (PCR)-based approaches for BSI diagnostics directly from whole blood, suffer from limitations such as inhibition leading to invalid results. In this retrospective study, we analyzed 23 parameters for their potential interference with LightCycler SeptiFast PCR tests (n = 2167) routinely performed at our institution. The overall inhibition rate was 9.1%. Test date, type of ward, procalcitonin levels, high leukocyte counts, and absolute neutrophil count were significantly associated with inhibition. For a subset (n = 448), cut-off values for leukocyte counts of < 5700 cells/µL and ≥ 26,900 cells/µL were significantly associated with a low (5%) and high (67%) inhibition risk. For patients with a moderate to high leukocyte count (5700-26,900 cells/µL), the additional administration of hydrocortisone significantly increased the inhibition risk. Furthermore, freezing of blood samples prior to DNA extraction and SF testing appeared to neutralize inhibitory factors. It remains to be investigated whether other molecular diagnostic tests are susceptible to similar inhibiting parameters.

Species Identification and Antibiotic Resistance Prediction by Analysis of Whole-Genome Sequence Data by Use of ARESdb: an Analysis of Isolates from the Unyvero Lower Respiratory Tract Infection Trial.

Whole-genome sequencing (WGS) is now routinely performed in clinical microbiology laboratories to assess isolate relatedness. With appropriately developed analytics, the same data can be used for prediction of antimicrobial susceptibility. We assessed WGS data for identification using open-source tools and antibiotic susceptibility testing (AST) prediction using ARESdb compared to matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) identification and broth microdilution phenotypic susceptibility testing on clinical isolates from a multicenter clinical trial of the FDA-cleared Unyvero lower respiratory tract infection (LRTI) application (Curetis). For the trial, more than 2,000 patient samples were collected from intensive care units across nine hospitals and tested for LRTI. The isolate subset used in this study included 620 clinical isolates originating from 455 LRTI culture-positive patient samples. Isolates were sequenced using the Illumina Nextera XT protocol and FASTQ files with raw reads uploaded to the ARESdb cloud platform (ares-genetics.cloud; released for research use in 2020). The platform combines Ares Genetics' proprietary database ARESdb with state-of-the-art bioinformatics tools and curated public data. For identification, WGS showed 99 and 93% concordance with MALDI-TOF MS at the genus and species levels, respectively. WGS-predicted susceptibility showed 89% categorical agreement with phenotypic susceptibility across a total of 129 species-compound pairs analyzed, with categorical agreement exceeding 90% in 78 species-compound pairs and reaching 100% in 32. Results of this study add to the growing body of literature showing that, with improvement of analytics, WGS data could be used to predict antimicrobial susceptibility.

Large-scale assessment of antimicrobial resistance marker databases for genetic phenotype prediction: a systematic review.

BACKGROUND: Antimicrobial resistance (AMR) is a rising health threat with 10 million annual casualties estimated by 2050. Appropriate treatment of infectious diseases with the right antibiotics reduces the spread of antibiotic resistance. Today, clinical practice relies on molecular and PCR techniques for pathogen identification and culture-based antibiotic susceptibility testing (AST). Recently, WGS has started to transform clinical microbiology, enabling prediction of resistance phenotypes from genotypes and allowing for more informed treatment decisions. WGS-based AST (WGS-AST) depends on the detection of AMR markers in sequenced isolates and therefore requires AMR reference databases. The completeness and quality of these databases are material to increase WGS-AST performance. METHODS: We present a systematic evaluation of the performance of publicly available AMR marker databases for resistance prediction on clinical isolates. We used the public databases CARD and ResFinder with a final dataset of 2587 isolates across five clinically relevant pathogens from PATRIC and NDARO, public repositories of antibiotic-resistant bacterial isolates. RESULTS: CARD and ResFinder WGS-AST performance had an overall balanced accuracy of 0.52 (±0.12) and 0.66 (±0.18), respectively. Major error rates were higher in CARD (42.68%) than ResFinder (25.06%). However, CARD showed almost no very major errors (1.17%) compared with ResFinder (4.42%). CONCLUSIONS: We show that AMR databases need further expansion, improved marker annotations per antibiotic rather than per antibiotic class and validated multivariate marker panels to achieve clinical utility, e.g. in order to meet performance requirements such as provided by the FDA for clinical microbiology diagnostic testing.

Comparing genome versus proteome-based identification of clinical bacterial isolates.

Whole-genome sequencing (WGS) is gaining importance in the analysis of bacterial cultures derived from patients with infectious diseases. Existing computational tools for WGS-based identification have, however, been evaluated on previously defined data relying thereby unwarily on the available taxonomic information.Here, we newly sequenced 846 clinical gram-negative bacterial isolates representing multiple distinct genera and compared the performance of five tools (CLARK, Kaiju, Kraken, DIAMOND/MEGAN and TUIT). To establish a faithful 'gold standard', the expert-driven taxonomy was compared with identifications based on matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry (MS) analysis. Additionally, the tools were also evaluated using a data set of 200 Staphylococcus aureus isolates.CLARK and Kraken (with k =31) performed best with 626 (100%) and 193 (99.5%) correct species classifications for the gram-negative and S. aureus isolates, respectively. Moreover, CLARK and Kraken demonstrated highest mean F-measure values (85.5/87.9% and 94.4/94.7% for the two data sets, respectively) in comparison with DIAMOND/MEGAN (71 and 85.3%), Kaiju (41.8 and 18.9%) and TUIT (34.5 and 86.5%). Finally, CLARK, Kaiju and Kraken outperformed the other tools by a factor of 30 to 170 fold in terms of runtime.We conclude that the application of nucleotide-based tools using k-mers-e.g. CLARK or Kraken-allows for accurate and fast taxonomic characterization of bacterial isolates from WGS data. Hence, our results suggest WGS-based genotyping to be a promising alternative to the MS-based biotyping in clinical settings. Moreover, we suggest that complementary information should be used for the evaluation of taxonomic classification tools, as public databases may suffer from suboptimal annotations.

Web-based NGS data analysis using miRMaster: a large-scale meta-analysis of human miRNAs.

The analysis of small RNA NGS data together with the discovery of new small RNAs is among the foremost challenges in life science. For the analysis of raw high-throughput sequencing data we implemented the fast, accurate and comprehensive web-based tool miRMaster. Our toolbox provides a wide range of modules for quantification of miRNAs and other non-coding RNAs, discovering new miRNAs, isomiRs, mutations, exogenous RNAs and motifs. Use-cases comprising hundreds of samples are processed in less than 5 h with an accuracy of 99.4%. An integrative analysis of small RNAs from 1836 data sets (20 billion reads) indicated that context-specific miRNAs (e.g. miRNAs present only in one or few different tissues / cell types) still remain to be discovered while broadly expressed miRNAs appear to be largely known. In total, our analysis of known and novel miRNAs indicated nearly 22 000 candidates of precursors with one or two mature forms. Based on these, we designed a custom microarray comprising 11 872 potential mature miRNAs to assess the quality of our prediction. MiRMaster is a convenient-to-use tool for the comprehensive and fast analysis of miRNA NGS data. In addition, our predicted miRNA candidates provided as custom array will allow researchers to perform in depth validation of candidates interesting to them.

Epigenome-Wide Association Study Identifies Cardiac Gene Patterning and a Novel Class of Biomarkers for Heart Failure.

BACKGROUND: Biochemical DNA modification resembles a crucial regulatory layer among genetic information, environmental factors, and the transcriptome. To identify epigenetic susceptibility regions and novel biomarkers linked to myocardial dysfunction and heart failure, we performed the first multi-omics study in myocardial tissue and blood of patients with dilated cardiomyopathy and controls. METHODS: Infinium human methylation 450 was used for high-density epigenome-wide mapping of DNA methylation in left-ventricular biopsies and whole peripheral blood of living probands. RNA deep sequencing was performed on the same samples in parallel. Whole-genome sequencing of all patients allowed exclusion of promiscuous genotype-induced methylation calls. RESULTS: In the screening stage, we detected 59 epigenetic loci that are significantly associated with dilated cardiomyopathy (false discovery corrected P≤0.05), with 3 of them reaching epigenome-wide significance at P≤5×10-8. Twenty-seven (46%) of these loci could be replicated in independent cohorts, underlining the role of epigenetic regulation of key cardiac transcription regulators. Using a staged multi-omics study design, we link a subset of 517 epigenetic loci with dilated cardiomyopathy and cardiac gene expression. Furthermore, we identified distinct epigenetic methylation patterns that are conserved across tissues, rendering these CpGs novel epigenetic biomarkers for heart failure. CONCLUSIONS: The present study provides to our knowledge the first epigenome-wide association study in living patients with heart failure using a multi-omics approach.

Background oriented schlieren measurement of the refractive index field of air induced by a hot, cylindrical measurement object.

To optically capture the topography of a hot measurement object with high precision, the light deflection by the inhomogeneous refractive index field-induced by the heat transfer from the measurement object to the ambient medium-has to be considered. We used the 2D background oriented schlieren method with illuminated wavelet background, an optical flow algorithm, and Ciddor's equation to quantify the refractive index field located directly above a red-glowing, hot measurement object. A heat transfer simulation has been implemented to verify the magnitude and the shape of the measured refractive index field. Provided that no forced external flow is disturbing the shape of the convective flow originating from the hot object, a laminar flow can be observed directly above the object, resulting in a sharply bounded, inhomogeneous refractive index field.

Using refraction in thick glass plates for optical path length modulation in low coherence interferometry.

In Michelson interferometer setups the standard way to generate different optical path lengths between a measurement arm and a reference arm relies on expensive high precision linear stages such as piezo actuators. We present an alternative approach based on the refraction of light at optical interfaces using a cheap stepper motor with high gearing ratio to control the rotation of a glass plate. The beam path is examined and a relation between angle of rotation and change in optical path length is devised. As verification, an experimental setup is presented, and reconstruction results from a measurement standard are shown. The reconstructed step height from this setup lies within 1.25% of the expected value.

Intact cell mass spectrometry as a progress tracking tool for batch and fed-batch fermentation processes.

Penicillin production during a fermentation process using industrial strains of Penicillium chrysogenum is a research topic permanently discussed since the accidental discovery of the antibiotic. Intact cell mass spectrometry (ICMS) can be a fast and novel monitoring tool for the fermentation progress during penicillin V production in a nearly real-time fashion. This method is already used for the characterization of microorganisms and the differentiation of fungal strains; therefore, the application of ICMS to samples directly harvested from a fermenter is a promising possibility to get fast information about the progress of fungal growth. After the optimization of the ICMS method to penicillin V fermentation broth samples, the obtained ICMS data were evaluated by hierarchical cluster analysis or an in-house software solution written especially for ICMS data comparison. Growth stages of a batch and fed-batch fermentation of Penicillium chrysogenum are differentiated by one of those statistical approaches. The application of two matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) instruments in the linear positive ion mode from different vendors demonstrated the universal applicability of the developed ICMS method. The base for a fast and easy-to-use method for monitoring the fermentation progress of P. chrysogenum is created with this ICMS method developed especially for fermentation broth samples.

Effect of albumin infusion on oxidative albumin modification and albumin binding capacity in chronic liver failure.

Oxidative albumin modification and impaired albumin binding function have been described both in chronic liver failure and for therapeutic albumin solutions. The aim of the present study was to evaluate the effect of albumin infusion on redox state and binding function of circulating albumin. We studied 20 patients with cirrhosis who routinely received albumin infusions for prevention of post-paracentesis circulatory dysfunction or treatment of hepatorenal syndrome. We measured albumin fractions by redox state of cysteine-34 and albumin binding properties using dansylsarcosine as site II ligand. Therapeutic albumin solutions showed high contents of human nonmercaptalbumin-1 and human nonmercaptalbumin-2, exceeding the respective values in our patients with decompensated cirrhosis. An initial protocol for the first nine patients sampled at baseline, 24 h and 48 h after albumin infusion revealed no significant changes of oxidized albumin species or albumin binding properties. However, a modified protocol for the remaining 11 patients sampled at baseline, <1 h after and 24 h after albumin infusion revealed short-lived changes of oxidized albumin species while no changes in albumin binding properties were observed. In conclusion, therapeutic albumin infusion transiently changed albumin redox state but did not improve binding function of circulating albumin in chronic liver failure.

Combining light microscopy, dielectric spectroscopy, MALDI intact cell mass spectrometry, FTIR spectromicroscopy and multivariate data mining for morphological and physiological bioprocess characterization of filamentous organisms.

Along with productivity and physiology, morphological growth behavior is the key parameter in bioprocess design for filamentous fungi. Lacking tools for fast, reliable and efficient analysis however, fungal morphology is still commonly tackled by empirical trial-and-error techniques during strain selection and process development procedures. Bridging the gap, this work presents a comprehensive analytical approach for morphological analysis combining automated high-throughput microscopy, multi-frequency dielectric spectroscopy, MALDI intact cell mass spectrometry and FTIR spectromicroscopy. Industrial fed-batch production processes were investigated in fully instrumented, automated bioreactors using the model system Penicillium chrysogenum. Physiological process characterization was based on the determination of specific conversion rates as scale-independent parameters. Conventional light microscopic morphological analysis was based on holistic determination of time series for more than 30 morphological parameters and their frequency distributions over the respective parameter range by automated high-throughput light microscopy. Characteristic protein patterns enriched in specific morphological and physiological states were further obtained by MALDI intact cell mass spectrometry. Spatial resolution of molecular biomass composition was facilitated by FTIR spectromicroscopy. Real-time in situ monitoring of morphological process behavior was achieved by linking multi-frequency dielectric spectroscopy with above outlined off-line methods. Data integration of complementing orthogonal techniques for morphological and physiological analysis together with multivariate modeling of interdependencies between morphology, physiology and process parameters facilitated complete bioprocess characterization. The suggested approach will thus help understanding morphological and physiological behavior and, in turn, allow to control and optimize those complex processes.

Reagent-free monitoring of multiple clinically relevant parameters in human blood plasma using a mid-infrared quantum cascade laser based sensor system.

We present a semi-automated point-of-care (POC) sensor approach for the simultaneous and reagent-free determination of clinically relevant parameters in blood plasma. The portable sensor system performed direct mid-infrared (MIR) transmission measurements of blood plasma samples using a broadly tunable external-cavity quantum cascade laser source with high spectral power density. This enabled the use of a flow cell with a long path length (165 µm) which resulted in high signal-to-noise ratios and a rugged system, insensitive to clogging. Multivariate calibration models were built using well established Partial-Least-Squares (PLS) regression analysis. Selection of spectral pre-processing procedures was optimized by an automated evaluation algorithm. Several analytes, including glucose, lactate, triglycerides, cholesterol, total protein as well as albumin, were successfully quantified in routinely taken blood plasma samples from 67 critically ill patients. Although relying on a spectral range from 1030 cm(-1) to 1230 cm(-1), which is optimal for glucose and lactate but rather unusual for protein analysis, it was possible to selectively determine the albumin and total protein concentrations with sufficient accuracy for POC application.

Cirrhosis is associated with lower serological responses to COVID-19 vaccines in patients with chronic liver disease.

Background & Aims: The response of patients with chronic liver disease (CLD) to COVID-19 vaccines remains unclear. Our aim was to assess the humoral immune response and efficacy of two-dose COVID-19 vaccines among patients with CLD of different aetiologies and disease stages. Methods: A total of 357 patients were recruited in clinical centres from six European countries, and 132 healthy volunteers served as controls. Serum IgG (nM), IgM (nM), and neutralising antibodies (%) against the Wuhan-Hu-1, B.1.617, and B.1.1.529 SARS-CoV-2 spike proteins were determined before vaccination (T0) and 14 days (T2) and 6 months (T3) after the second-dose vaccination. Patients fulfilling inclusion criteria at T2 (n = 212) were stratified into 'low' or 'high' responders according to IgG levels. Infection rates and severity were collected throughout the study. Results: Wuhan-Hu-1 IgG, IgM, and neutralisation levels significantly increased from T0 to T2 in patients vaccinated with BNT162b2 (70.3%), mRNA-1273 (18.9%), or ChAdOx1 (10.8%). In multivariate analysis, age, cirrhosis, and type of vaccine (ChAdOx1 > BNT162b2 > mRNA-1273) predicted 'low' humoral response, whereas viral hepatitis and antiviral therapy predicted 'high' humoral response. Compared with Wuhan-Hu-1, B.1.617 and, further, B.1.1.529 IgG levels were significantly lower at both T2 and T3. Compared with healthy individuals, patients with CLD presented with lower B.1.1.529 IgGs at T2 with no additional key differences. No major clinical or immune IgG parameters associated with SARS-CoV-2 infection rates or vaccine efficacy. Conclusions: Patients with CLD and cirrhosis exhibit lower immune responses to COVID-19 vaccination, irrespective of disease aetiology. The type of vaccine leads to different antibody responses that appear not to associate with distinct efficacy, although this needs validation in larger cohorts with a more balanced representation of all vaccines. Impact and Implications: In patients with CLD vaccinated with two-dose vaccines, age, cirrhosis, and type of vaccine (Vaxzevria > Pfizer BioNTech > Moderna) predict a 'lower' humoral response, whereas viral hepatitis aetiology and prior antiviral therapy predict a 'higher' humoral response. This differential response appears not to associate with SARS-CoV-2 infection incidence or vaccine efficacy. However, compared with Wuhan-Hu-1, humoral immunity was lower for the Delta and Omicron variants, and all decreased after 6 months. As such, patients with CLD, particularly those older and with cirrhosis, should be prioritised for receiving booster doses and/or recently approved adapted vaccines.

A novel method for fast and statistically verified morphological characterization of filamentous fungi.

Along with productivity and physiology, morphological growth behavior is the key parameter in bioprocess design for filamentous fungi. Despite complex interactions between fungal morphology, broth viscosity, mixing kinetics, transport characteristics and process productivity, morphology is still commonly tackled only by empirical trial-and-error techniques during strain selection and process development procedures. In fact, morphological growth characteristics are investigated by computational analysis of only a limited number of pre-selected microscopic images or via manual evaluation of images, which causes biased results and does not allow any automation or high-throughput quantification. To overcome the lack of tools for fast, reliable and quantitative morphological analysis, this work introduces a method enabling statistically verified quantification of fungal morphology in accordance with Quality by Design principles. The novel, high-throughput method presented here interlinks fully automated recording of microscopic images with a newly developed evaluation approach reducing the need for manual intervention to a minimum. Validity of results is ensured by concomitantly testing the acquired sample for representativeness by statistical inference via bootstrap analysis. The novel approach for statistical verification can be equally applied as control logic to automatically proceed with morphological analysis of a consecutive sample once user defined acceptance criteria are met. Hence, analysis time can be reduced to an absolute minimum. The quantitative potential of the developed methodology is demonstrated by characterizing the morphological growth behavior of two industrial Penicillium chrysogenum production strains in batch cultivation.

Switching industrial production processes from complex to defined media: method development and case study using the example of Penicillium chrysogenum.

BACKGROUND: Filamentous fungi are versatile cell factories and widely used for the production of antibiotics, organic acids, enzymes and other industrially relevant compounds at large scale. As a fact, industrial production processes employing filamentous fungi are commonly based on complex raw materials. However, considerable lot-to-lot variability of complex media ingredients not only demands for exhaustive incoming components inspection and quality control, but unavoidably affects process stability and performance. Thus, switching bioprocesses from complex to defined media is highly desirable. RESULTS: This study presents a strategy for strain characterization of filamentous fungi on partly complex media using redundant mass balancing techniques. Applying the suggested method, interdependencies between specific biomass and side-product formation rates, production of fructooligosaccharides, specific complex media component uptake rates and fungal strains were revealed. A 2-fold increase of the overall penicillin space time yield and a 3-fold increase in the maximum specific penicillin formation rate were reached in defined media compared to complex media. CONCLUSIONS: The newly developed methodology enabled fast characterization of two different industrial Penicillium chrysogenum candidate strains on complex media based on specific complex media component uptake kinetics and identification of the most promising strain for switching the process from complex to defined conditions. Characterization at different complex/defined media ratios using only a limited number of analytical methods allowed maximizing the overall industrial objectives of increasing both, method throughput and the generation of scientific process understanding.