Microbial Cell Factories / Induction without methanol: novel regulated promoters enable high-level expression in Pichia pastoris

Background: Inducible high-level expression is favoured for recombinant protein production in Pichia pastoris. Therefore, novel regulated promoters are desired, ideally repressing heterologous gene expression during initial growth and enabling it in the production phase. In a typical large scale fed-batch culture repression is desired during the batch phase where cells grow on a surplus of e.g. glycerol, while heterologous gene expression should be active in the feed phase under carbon (e.g. glucose) limitation. Results: DNA microarray analysis of P. pastoris wild type cells growing in glycerol-based batch and glucose-based fed batch was used for the identification of genes with both, strong repression on glycerol and high-level expression in the feed phase. Six novel glucose-limit inducible promoters were successfully applied to express the intracellular reporter eGFP. The highest expression levels together with strong repression in pre-culture were achieved with the novel promoters PG1 and PG6. Human serum albumin (HSA) was used to characterize the promoters with an industrially relevant secreted protein. A PG1 clone with two gene copies reached about 230% of the biomass specific HSA titer in glucose-based fed batch fermentation compared to a PGAP clone with identical gene copy number, while PG6 only achieved 39%. Two clones each carrying eleven gene copies, expressing HSA under control of PG1 and PG6 respectively were generated by post-transformational vector amplification. They produced about 1.0 and 0.7 g L-1 HSA respectively in equal fed batch processes. The suitability in production processes was also verified with HyHEL antibody Fab fragment for PG1 and with porcine carboxypeptidase B for PG6. Moreover, the molecular function of the gene under the control of PG1 was determined to encode a high-affinity glucose transporter and named GTH1. Conclusions: A set of novel regulated promoters, enabling induction without methanol, was successfully identified by using DNA microarrays and shown to be suitable for high level expression of recombinant proteins in glucose-based protein production processes

SALSA PICANTE: a machine learning attack on LWE with binary secrets

Learning with Errors (LWE) is a hard math problem underpinning many proposed post-quantum cryptographic (PQC) systems. The only PQC Key Exchange Mechanism (KEM) standardized by NIST is based on module~LWE, and current publicly available PQ Homomorphic Encryption (HE) libraries are based on ring LWE. The security of LWE-based PQ cryptosystems is critical, but certain implementation choices could weaken them. One such choice is sparse binary secrets, desirable for PQ HE schemes for efficiency reasons. Prior work, SALSA, demonstrated a machine learning-based attack on LWE with sparse binary secrets in small dimensions ($n \le 128$) and low Hamming weights ($h \le 4$). However, this attack assumes access to millions of eavesdropped LWE samples and fails at higher Hamming weights or dimensions. We present PICANTE, an enhanced machine learning attack on LWE with sparse binary secrets, which recovers secrets in much larger dimensions (up to $n=350$) and with larger Hamming weights (roughly $n/10$, and up to $h=60$ for $n=350$). We achieve this dramatic improvement via a novel preprocessing step, which allows us to generate training data from a linear number of eavesdropped LWE samples ($4n$) and changes the distribution of the data to improve transformer training. We also improve the secret recovery methods of SALSA and introduce a novel cross-attention recovery mechanism allowing us to read off the secret directly from the trained models. While PICANTE does not threaten NIST\u27s proposed LWE standards, it demonstrates significant improvement over SALSA and could scale further, highlighting the need for future investigation into machine learning attacks on LWE with sparse binary secrets

Nachhaltigkeit im industriellen Umfeld

Im Rahmen der Lehrveranstaltung "Nachhaltigkeit im industriellen Umfeld" im Masterstudiengang Umwelt- und Verfahrenstechnik der Hochschulen Konstanz und Ravensburg-Weingarten wurde 2015 eine studentische Fachkonferenz durchgeführt. Die Studierenden entwickelten in Einzelarbeit oder als Zweierteam Konferenzbeiträge zu folgenden Themen: - Innovationen und Spannendes aus dem Bereich der Energieerzeugung und -wandlung - Aspekte der Schließung von Stoffkreisläufen und Vermeidung von Schadstoffeinträgen in die Umwelt - Chancen und Herausforderungen Nachwachsender Rohstoffe bei verschiedenen Einsatzmöglichkeiten sowie Themen der Nachhaltigkeit in der Landwirtschaft - verschiedene Blickwinkel auf das Thema Wasser (von der Abwasserreinigung bis zum Wasserkonsum der Konsumenten) - die Betrachtung spezifischer Industrien und Unternehmen sowie deren Werkzeuge zur Umsetzung von Nachhaltigkeit Die Ergebnisse der studentischen Fachkonferenz zur „Nachhaltigkeit im industriellen Umfeld“ werden in der vorliegenden Publikation präsentiert

The Need for Sustainability, Equity, and International Exchange: Perspectives of Early Career Environmental Psychologists on the Future of Conferences.

At the 2019 and 2021 International Conference on Environmental Psychology, discussions were held on the future of conferences in light of the enormous greenhouse gas emissions and inequities associated with conference travel. In this manuscript, we provide an early career researcher (ECR) perspective on this discussion. We argue that travel-intensive conference practices damage both the environment and our credibility as a discipline, conflict with the intrinsic values and motivations of our discipline, and are inequitable. As such, they must change. This change can be achieved by moving toward virtual and hybrid conferences, which can reduce researchers' carbon footprints and promote equity, if employed carefully and with informal exchange as a priority. By acting collectively and with the support of institutional change, we can adapt conference travel norms in our field. To investigate whether our arguments correspond to views in the wider community of ECRs within environmental psychology, we conducted a community case study. By leveraging our professional networks and directly contacting researchers in countries underrepresented in those networks, we recruited 117 ECRs in 32 countries for an online survey in February 2022. The surveyed ECRs supported a change in conference travel practices, including flying less, and perceived the number of researchers wanting to reduce their travel emissions to be growing. Thirteen percent of respondents had even considered leaving academia due to travel requirements. Concerning alternative conference formats, a mixed picture emerged. Overall, participants had slightly negative evaluations of virtual conferences, but expected them to improve within the next 5 years. However, ECRs with health issues, facing visa challenges, on low funding, living in remote areas, with caretaking obligations or facing travel restrictions due to COVID-19 expected a switch toward virtual or hybrid conferences to positively affect their groups. Participants were divided about their ability to build professional relationships in virtual settings, but believed that maintaining relationships virtually is possible. We conclude by arguing that the concerns of ECRs in environmental psychology about current and alternative conference practices must be taken seriously. We call on our community to work on collective solutions and less travel-intensive conference designs using participatory methods. [Abstract copyright: Copyright © 2022 Köhler, Kreil, Wenger, Darmandieu, Graves, Haugestad, Holzen, Keller, Lloyd, Marczak, Međugorac and Rosa.

A multi-platform reference for somatic structural variation detection

Accurate detection of somatic structural variation (SV) in cancer genomes remains a challenging problem. This is in part due to the lack of high-quality, gold-standard datasets that enable the benchmarking of experimental approaches and bioinformatic analysis pipelines. Here, we performed somatic SV analysis of the paired melanoma and normal lymphoblastoid COLO829 cell lines using four different sequencing technologies. Based on the evidence from multiple technologies combined with extensive experimental validation, we compiled a comprehensive set of carefully curated and validated somatic SVs, comprising all SV types. We demonstrate the utility of this resource by determining the SV detection performance as a function of tumor purity and sequence depth, highlighting the importance of assessing these parameters in cancer genomics projects. The truth somatic SV dataset as well as the underlying raw multi-platform sequencing data are freely available and are an important resource for community somatic benchmarking efforts

SALSA PICANTE: a machine learning attack on LWE with binary secrets

Learning with Errors (LWE) is a hard math problem underpinning many proposed post-quantum cryptographic (PQC) systems. The only PQC Key Exchange Mechanism (KEM) standardized by NIST is based on module~LWE, and current publicly available PQ Homomorphic Encryption (HE) libraries are based on ring LWE. The security of LWE-based PQ cryptosystems is critical, but certain implementation choices could weaken them. One such choice is sparse binary secrets, desirable for PQ HE schemes for efficiency reasons. Prior work, SALSA, demonstrated a machine learning-based attack on LWE with sparse binary secrets in small dimensions ($n \le 128$) and low Hamming weights ($h \le 4$). However, this attack assumes access to millions of eavesdropped LWE samples and fails at higher Hamming weights or dimensions. We present PICANTE, an enhanced machine learning attack on LWE with sparse binary secrets, which recovers secrets in much larger dimensions (up to $n=350$) and with larger Hamming weights (roughly $n/10$, and up to $h=60$ for $n=350$). We achieve this dramatic improvement via a novel preprocessing step, which allows us to generate training data from a linear number of eavesdropped LWE samples ($4n$) and changes the distribution of the data to improve transformer training. We also improve the secret recovery methods of SALSA and introduce a novel cross-attention recovery mechanism allowing us to read off the secret directly from the trained models. While PICANTE does not threaten NIST's proposed LWE standards, it demonstrates significant improvement over SALSA and could scale further, highlighting the need for future investigation into machine learning attacks on LWE with sparse binary secrets.Comment: 15 pages, 6 figures, 17 table

Distinct increased outliers among 136 rectal cancer patients assessed by γ\gammaH2AX

Background: In recent years attention has focused on $\gamma$H2AX as a very sensitive double strand break indicator. It has been suggested that $\gamma$H2AX might be able to predict individual radiosensitivity. Our aim was to study the induction and repair of DNA double strand breaks labelled by $\gamma$H2AX in a large cohort. Methods: In a prospective study lymphocytes of 136 rectal cancer (RC) patients and 59 healthy individuals were ex vivo irradiated (IR) and initial DNA damage was compared to remaining DNA damage after 2 Gy and 24 hours repair time and preexisting DNA damage in unirradiated lymphocytes. Lymphocytes were immunostained with anti-$\gamma$H2AX antibodies and microscopic images with an extended depth of field were acquired. $\gamma$H2AX foci counting was performed using a semi-automatic image analysis software. Results: Distinct increased values of preexisting and remaining $\gamma$H2AX foci in the group of RC patients were found compared to the healthy individuals. Additionally there are clear differences within the groups and there are outliers in about 12% of the RC patients after ex vivo IR. Conclusions: The $\gamma$H2AX assay has the capability to identify a group of outliers which are most probably patients with increased radiosensitivity having the highest risk of suffering radiotherapy-related late sequelae