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Summary: This longitudinal wait-list control group study aims to evaluate the effectiveness of different formats of a stress management intervention (face-to-face vs. online) on stress, burnout symptoms and work engagement before, shortly after intervention and at a six-weeks follow-up. Moreover, the underlying mechanisms such as job crafting, personality and baseline stress level will be investigated. Subjects will be assigned to groups by randomization. Hypotheses will be tested using analysis of variance and path analysis. The practical benefit of this study is to increase knowledge about different formats of stress prevention and to use these findings to improve risk assessments and the occupational health management in organizations as well as to gain more insights into who benefits most from stress prevention programs. Theoretical background: Currently, stress increases among the working population (Korn Ferry Studie, 2018). This is particularly noticeable in industrialized nations such as Germany, where work densification has increased in recent years due to digitalization (Bundesministerium für Arbeit und Soziales [BMAS], 2017): Every second German reports stress-related impairments (Techniker Krankenkasse, 2021). Especially in public service organizations work-related stressors are more likely to appear and the structural level of risk of work-related stress is higher than in other organizational settings (De Simone et al., 2016). Prolonged stress can have negative effects on physical health, e.g. immune suppression (Rensing et al., 2005) and high blood pressure (Gehring & Klein, 2015), and mental illnesses can be the consequence, e.g. depression (Chen et al., 2009). In addition to physical and mental health impairments, chronic stress can weaken the economic success of companies through absenteeism, presenteeism or terminations (Hassard et al., 2018; Kalia, 2002). Thus, stress management and occupational health management are gaining in importance. However, there is a discrepancy between the high demand and low utilization of stress management interventions (Gesetzliche Krankenversicherung [GKV]-Spitzenverband & Medizinischer Dienst des Spitzenverbandes Bund der Krankenkassen [MDS], 2018). In current times of digitalization, digital formats become more attractive as they are more accessible, available at any time and cost saving (Kuster et al., 2017). Nevertheless, face-to-face interventions are often preferred because of the personal interaction between trainer and participants and the high degree of task clarity (Chen & Jones, 2007). Varying research findings on the effectiveness of face-to-face and online formats exist (Chen & Jones, 2007). The purpose of this study is to evaluate the effectiveness of different formats of a stress management intervention in the public sector to reduce participants´ stress level and burnout symptoms as well to increase participants´ work engagement. Another focus is on understanding underlying mechanisms of the effect model to improve stress prevention offers for occupational health management in organizations. Study goals: The study aims to evaluate the effectiveness of different formats of a stress management intervention (face-to-face vs. online) on stress, burnout symptoms and work engagement compared to a wait-list control group in the public sector. Furthermore, it will be tested if effects remain stable at a six-weeks follow-up. Moreover, underlying mechanisms such as job crafting, personality and baseline stress level will be investigated by conducting a path analysis. Hypotheses: 1. Participants of the two intervention groups (face-to-face, online) show significantly reduced (a) perceived stress and (b) emotional exhaustion and (c) significantly more work engagement from baseline to post-treatment shortly after the intervention and at a six-weeks follow-up compared to the wait-list control group. 2. Participants of the face-to-face intervention show a stronger (a) decrease in perceived stress and (b) increase in work engagement compared to participants of the online course. 3. Participants' levels of baseline stress moderate the effect of the stress management intervention (face-to-face, online) on (a) perceived stress, (b) emotional exhaustion and (c) work engagement. 4. Participants' levels of (a) extraversion and (b) neuroticism moderate the effect of the stress management intervention (face-to-face, online) on perceived stress. 5. The effect of the online course on perceived stress is mediated by (a) structural job crafting, and not by challenging job crafting (b) and social job crafting (c). 6. The effect of the face-to-face training on perceived stress is mediated by (a) structural job crafting, (b) challenging job crafting (c) and social job crafting. Study Design: The study will use a wait-list control group design with three points of measurement. The 3x3 design consists of the within-factor time and the between-factor group, which is the manipulated variable. Self-report data will be assessed via online questionnaires using LimeSurvey Version 5.3.19 (Limesurvey GmbH, 2022) at baseline before the intervention (T1), shortly after the intervention (T2) and at a follow-up six weeks after T2 (T3). These three points of measurement allow conclusions about short-term and long-term effects. The participants will be assigned to one out of three groups by randomization: Face-to-face training (Group 1), online course (Group 2) and wait-list control group (Group 3). Group 1 will participate in a face-to-face stress management training for one day. Group 2 will participate in an online stress management course for five weeks. Participants of Group 3 will receive no intervention at first but will get free access to the face-to-face training or the online course once the last survey is conducted. In addition to the online survey, voluntary meetings are offered at T1, T2 and T3 to all participants of the three groups to provide a space for questions, exchange opportunities and to reduce the drop-out rate. The intervention investigated is the stress management course “Einfach weniger Stress” (Paulsen & Kortsch, 2020). “Einfach weniger Stress” is a scientifically evaluated stress prevention program that helps participants to develop stress management skills in order to reduce their stress level and increase serenity in the long term. The course concept is based on psychological theories such as the Job Demands-Resources Model (Demerouti et al., 2001) and the Transactional Model of Stress (Lazarus & Folkman, 1987). Currently, a face-to-face training and an online self-learning course exist for this stress management program. So far, both formats have been scientifically evaluated in separate studies. “Einfach weniger Stress” consists of five main modules which have been supplemented by an introductory module and a final reflection module for the online course. The five main modules focus on understanding what stress is, recognizing one’s own stressors, activating one’s resources, planning the implementation of action plans and remaining able to act calmly even in the face of barriers. Measured variables: Primary outcome will be perceived stress (Perceived Stress Scale-10, Cohen et al., 1983; German version from Schneider et al., 2020). Secondary outcomes will include work engagement (Utrecht Work Engagement Scale-9, Schaufeli & Bakker, 2003; Schaufeli et al., 2006) and emotional exhaustion (Maslach-Burnout-Inventory, Büssing & Perrar, 1992). In addition, job crafting (Job Crafting Scale, Lichtenthaler & Fischbach, 2016; Tims et al., 2012) will be surveyed as well as satisfaction with the stress management format by a self-constructed one-item-measure. Furthermore, personality (Big-Five-Inventory-10, Rammstedt et al., 2013) and sociodemographic data including gender, age, group and an anonymous participant code will be assessed to T1. Participant recruitment, selection and compensation: The study will be conducted in a medium sized company from the German public sector in the division of economic affairs and energy. Participation is voluntary, free of charge and accessible to all employees. Acquisition will take place via intranet, email distribution lists and flyers. In order to participate in the stress management program, participants must agree to the privacy statement and an informed consent form. The project has been agreed with the General Staff Council and Data Protection Officer and has been approved by the Ethics Committee. Participants will receive the online questionnaires via email. Participants will not get any compensation but free access to the stress management course. The training and the online course can be done during working hours. Study procedures: After registration participants will be randomized to one out of three groups and informed via email. After a voluntary kick-off, participants will complete their first online questionnaire before their stress management intervention begins. Every participant, regardless of their group, will fill out three online questionnaires to provide self-report data at baseline before the intervention (T1), shortly after the intervention (T2) and at a six-weeks follow-up (T3). At the time of questionnaires T2 and T3 the voluntary reflection meetings will be offered. Participants who cannot be present at the reflection meeting will receive all necessary information by email. After the last time point of measurement the participants of the wait-list control group will get free access to the face-to-face training or the online course. Handling of participant drop-out: There will not be any special treatment for participants who drop out. Candidates will not be replaced. Analysis Plan: The collected data will be analyzed using IBM SPSS Statistics and R 4.2.1. At first descriptives will be computed for every variable. Postulated hypotheses based on the 3x3 design with repeated measures on both factors will be tested using analysis of variance. If, contrary to expectations, there are large differences in the baseline stress levels, an analysis of covariance will be used instead of the analysis of variance in order to remove baseline stress as a covariate. Path analysis and multiple regressions will be conducted to test indirect mediating and moderating effects. Contributors: Runa Fasthoff, Technische Universität Braunschweig Lea Nolte, Technische Universität Braunschweig Prof. Dr. Beate Muschalla, Technische Universität Braunschweig Prof. Dr. Timo Kortsch, Denkverstärker GbR Date of preregistration: 12.07.2022, registration prior to creation of data Estimated duration of the project: 6 months Conflict of interest statement: Prof. Dr. Timo Kortsch is the developer of the stress management program “Einfach weniger Stress” and profits from the sales of the face-to-face training and the online course. However, he acts according to the Ethical Principles of Psychologists and Code of Conduct from the Federation of German Psychologist Associations (DGPs). References: Bundesministerium für Arbeit und Soziales [BMAS]. (2017). Weißbuch Arbeiten 4.0. https://www.bmas.de/SharedDocs/Downloads/DE/Publikationen/a883-weissbuch.pdf?__blob=publicationFile&v=1 Büssing, A., & Perrar, K. M. (1992). Die Messung von Burnout. 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Background The demand for biobased polymers is increasing steadily worldwide. Microbial hosts for production of their monomeric precursors such as glutarate are developed. To meet the market demand, production hosts have to be improved constantly with respect to product titers and yields, but also shortening bioprocess duration is important. Results In this study, adaptive laboratory evolution was used to improve a C. glutamicum strain engineered for production of the C5-dicarboxylic acid glutarate by flux enforcement. Deletion of the l-glutamic acid dehydrogenase gene gdh coupled growth to glutarate production since two transaminases in the glutarate pathway are crucial for nitrogen assimilation. The hypothesis that strains selected for faster glutarate-coupled growth by adaptive laboratory evolution show improved glutarate production was tested. A serial dilution growth experiment allowed isolating faster growing mutants with growth rates increasing from 0.10 h−1 by the parental strain to 0.17 h−1 by the fastest mutant. Indeed, the fastest growing mutant produced glutarate with a twofold higher volumetric productivity of 0.18 g L−1 h−1 than the parental strain. Genome sequencing of the evolved strain revealed candidate mutations for improved production. Reverse genetic engineering revealed that an amino acid exchange in the large subunit of l-glutamic acid-2-oxoglutarate aminotransferase was causal for accelerated glutarate production and its beneficial effect was dependent on flux enforcement due to deletion of gdh. Performance of the evolved mutant was stable at the 2 L bioreactor-scale operated in batch and fed-batch mode in a mineral salts medium and reached a titer of 22.7 g L−1, a yield of 0.23 g g−1 and a volumetric productivity of 0.35 g L−1 h−1. Reactive extraction of glutarate directly from the fermentation broth was optimized leading to yields of 58% and 99% in the reactive extraction and reactive re-extraction step, respectively. The fermentation medium was adapted according to the downstream processing results. Conclusion Flux enforcement to couple growth to operation of a product biosynthesis pathway provides a basis to select strains growing and producing faster by adaptive laboratory evolution. After identifying candidate mutations by genome sequencing causal mutations can be identified by reverse genetics. As exemplified here for glutarate production by C. glutamicum, this approach allowed deducing rational metabolic engineering strategies. Supplementary Information The online version contains supplementary material available at 10.1186/s12934-021-01586-3.

Additional file 1: Figure S1. (A) DNA region of the plasmid pEC-XT99A-gabTDP134L with the 21 bp sequence deleted in ALE strain GluA T7 (boxed in red). (B) Determination of the minimum inhibitory concentration for tetracycline for strain GluA T0 with the orginal plasmid pEC-XT99A-gabTDP134L and GluA RG1 carrying this plasmid with the 21 bp deletion. Cells were grown in Duetz cultivation system using BHIS supplemented with increasing concentrations of tetracycline (0–80 µg µL−1). The ΔOD600 values were determined after 48 hours and are shown as means with standard deviations (n = 3 cultivations). Figure S2. Dependence of the specific acitvity of GOGAT on the glutamine concentration determined for GRLys1ΔgltB overexpressing the native version of gltBD (A) or the mutated gltBE686QD (B). Crude extracts of GRLys1ΔgltB (pEKEx3-gltBD) and GRLys1ΔgltB (pEKEx3-gltBE686QD) were assayed for specific activity of the glutamate synthase (GOGAT) in the presence of increasing glutamine concentrations (0 mM, 0.1 mM, 0.25 mM, 0.5 mM, 0.75 mM, 1 mM, 2 mM, 5 mM, 10 mM). Values represent means and standard deviations of triplicate measurements. Figure S3. Glutarate production by GluA T7 in chloride-free medium. Cells were grown in Duetz cultivation system using either standard CGXII minimal medium or CGXII minimal medium without chloride supplemented with 40 g L−1 glucose, induced with 1 mM IPTG, and harvested after 48 h. Values and error bars represent means and standard deviations of glutarate (green) and 5AVA concentrations (red) in the culture supernatants (n = 3 cultivations).