Engineering in Life Sciences最新文献

Microbiome research has become increasingly prominent, as scientists explore the intricately assembled microbial communities (i.e., microbiota) and their wide-ranging impacts on human systems (e.g., health and foods), environmental sustainability (bioremediation, biogeochemistry, and ecosystem biorestoration, or 3B for Sustainability), and next-generation bioeconomy (i.e., bioenergy, biomedicine, and biomaterials, or 3B for Resources). This burgeoning field has been driven by the widespread adoption of meta-omics methodologies, such as metagenomics, metatranscriptomics, metaproteomics, and metabolomics. In this special issue, we present a compendium of recent human and environmental microbiome studies that elucidate the multifaceted roles of microbial communities and their implications across different domains of research in life sciences and related fields of application.

The gut microbiome stands out as a central player in human health, influencing fundamental physiological processes such as digestion, immunity, and metabolism. Tang et al. delves into the intricate interplay between the gut microbiota and the host epigenome in the context of Non-alcoholic Fatty Liver Disease (NAFLD), shedding light on how microbial factors can modulate gene expression patterns associated with NAFLD pathogenesis [1]. Similarly, Zoghi et al. investigate the association between gut dysbiosis and nutritional imbalances in children, underscoring the potential therapeutic avenues for modulating gut microbiota composition to restore energy homeostasis [2].

Moreover, the symbiotic interplay between flavonoids and the gut microbiota emerges as a promising area of study in maintaining metabolic balance and overall health by Zhou et al. [3]. Flavonoids, abundant in fruits and vegetables, serve as essential dietary components that undergo biotransformation by gut microbes, yielding bioactive metabolites with various health-promoting properties. Understanding this intricate interplay opens new avenues for leveraging dietary interventions to modulate gut microbiota composition and enhance metabolic health (Figure 1).

Beyond human health, microbial communities also play critical roles in environmental processes, particularly in the biodegradation of pollutants. Huang et al. leverage meta-omics approaches to uncover the genetic potential of microbial communities in contaminated environments, offering insights into potential bioremediation strategies for mitigating environmental pollution [4].

Furthermore, microbiomes offer promising avenues for bioconversion and biodegradation processes in the context of biotechnology and industrial applications. Zhu et al. investigate the dynamics of microbial consortia during primary sludge and food waste fermentation, revealing insights into how different environmental conditions and additives can modulate fermentation product profiles [5]. The study

Cell engineering strategies typically rely on energy-consuming overexpression of genes or radical gene-knock out. Both strategies are not particularly convenient for the generation of slightly modulated phenotypes, as needed in biosimilar development of for example differentially fucosylated monoclonal antibodies (mAbs). Recently, transiently transfected small noncoding microRNAs (miRNAs), known to be regulators of entire gene networks, have emerged as potent fucosylation modulators in Chinese hamster ovary (CHO) production cells. Here, we demonstrate the applicability of stable miRNA overexpression in CHO production cells to adjust the fucosylation pattern of mAbs as a model phenotype. For this purpose, we applied a miRNA chaining strategy to achieve adjustability of fucosylation in stable cell pools. In addition, we were able to implement recently developed artificial miRNAs (amiRNAs) based on native miRNA sequences into a stable CHO expression system to even further fine-tune fucosylation regulation. Our results demonstrate the potential of miRNAs as a versatile tool to control mAb fucosylation in CHO production cells without adverse side effects on important process parameters.

Shake flask cultivation, a cornerstone in bioprocess research encounters limitations in supplying sufficient oxygen and exchanging gases, restricting its accuracy in assessing microbial growth and metabolic activity. In this communication, we introduce an innovative gas supply apparatus that harnesses the rotational motion of a shaking incubator to facilitate continuous air delivery, effectively overcoming these limitations. We measured the mass transfer coefficient (k_La) and conducted batch cultures of Corynebacterium glutamicum H36LsGAD using various working volumes to assess its performance. Results demonstrated that the gas supply apparatus significantly outperforms conventional silicone stoppers regarding oxygen delivery, with k_La values of 2531.7 h⁻¹ compared to 20.25 h⁻¹ at 230 rpm. Moreover, in batch cultures, the gas supply apparatus enabled substantial improvements in microbial growth, maintaining exponential growth even at larger working volumes. Compared to the existing system, an increase in final cell mass by a factor of 3.4-fold was observed when utilizing 20% of the flask's volume, and a remarkable 9-fold increase was achieved when using 60%. Furthermore, the gas supply apparatus ensured consistent oxygen supply and efficient gas exchange within the flask, overcoming challenges associated with low working volumes. This approach offers a simple yet effective solution to enhance gas transfer in shake flask cultivation, bridging the gap between laboratory-scale experiments and industrial fermenters. Its broad applicability holds promise for advancing research in bioprocess optimization and scale-up endeavors.

Bioreactor scale-up and scale-down have always been a topical issue for the biopharmaceutical industry and despite considerable effort, the identification of a fail-safe strategy for bioprocess development across scales remains a challenge. With the ubiquitous growth of digital transformation technologies, new scaling methods based on computer models may enable more effective scaling. This study aimed to evaluate the potential application of machine learning (ML) algorithms for bioreactor scale-up, with a specific focus on the prediction of scaling parameters. Factors critical to the development of such models were identified and data for bioreactor scale-up studies involving CHO cell-generated mAb products collated from the literature and public sources for the development of unsupervised and supervised ML models. Comparison of bioreactor performance across scales identified similarities between the different processes and primary differences between small- and large-scale bioreactors. A series of three case studies were developed to assess the relationship between cell growth and scale-sensitive bioreactor features. An embedding layer improved the capability of artificial neural network models to predict cell growth at a large-scale, as this approach captured similarities between the processes. Further models constructed to predict scaling parameters demonstrated how ML models may be applied to assist the scaling process. The development of data sets that include more characterization data with greater variability under different gassing and agitation regimes will also assist the future development of ML tools for bioreactor scaling.

Microplastics (MPs) are major concern due to their potential harm to ecosystems and most research has focused on their presence and fate, with limited attention to their biodegradation in aquatic ecosystems. Nevertheless, MPs act as hotspots for the colonization by a diverse range of microorganisms that can adhere to plastic surfaces, resulting in the subsequent formation of biofilms—a potential threat especially in terms of pathogenicity. This study employed 16S rRNA and 18S rRNA sequencing metagenomic analyses to investigate microbial communities within biofilms on plastic materials exposed to long-term marine and freshwater environments. Three Arcobacter species (Arcobacter nitrofigilis, Arcobacter acticola, and Arcobacter suis) emerged as dominant species in M_MP sample, while Flavobacterium tructae was the predominant species within the F_MP sample. The 18S rRNA sequencing revealed the presence of the fungal phylum Ascomycota and the microalgal species Pseudocharaciopsis ovalis in F_MP. Although, the primary species detected on M_MP and F_MP samples include bacteria previously implicated as pathogen, the predominant species identified in this study were unconnected to MP-associated biofilms or MP degradation. Their presence constitutes a novel discovery, opening promising avenues for the exploration of their potential involvement in the biodegradation of MPs within aquatic environments.

Polyhydroxyalkanoates (PHAs) have gained interest recently due to their biodegradability and versatility. In particular, the chemical compositions of medium-chain-length (mcl)-PHAs are highly diverse, comprising different monomers containing 6–14 carbon atoms. This review summarizes different feedstocks and fermentation strategies to enhance mcl-PHA production and briefly discusses the downstream processing. This review also provides comprehensive details on analytical tools for determining the composition and properties of mcl-PHA. Moreover, this study provides novel information by statistically analyzing the data collected from several reports on mcl-PHA to determine the optimal fermentation parameters (specific growth rate, PHA productivity, and PHA yield from various structurally related and unrelated substrates), mcl-PHA composition, molecular weight (MW), and thermal and mechanical properties, in addition to other relevant statistical values. The analysis revealed that the median PHA productivity observed in the fed-batch feeding strategy was 0.4 g L⁻¹ h⁻¹, which is eight times higher than that obtained from batch feeding (0.05 g L⁻¹ h⁻¹). Furthermore, 3-hydroxyoctanoate and -decanoate were the primary monomers incorporated into mcl-PHA. The investigation also determined the median glass transition temperature (−43°C) and melting temperature (47°C), which indicated that mcl-PHA is a flexible amorphous polymer at room temperature with a median MW of 104 kDa. However, information on the monomer composition or heterogeneity and the associated physical and mechanical data of mcl-PHAs is inadequate. Based on their mechanical values, the mcl-PHAs can be classified as semi-crystalline polymers (median crystallinity 23%) with rubber-like properties and a median elongation at break of 385%. However, due to the limited mechanical data available for mcl-PHAs with known monomer composition, identifying suitable processing tools and applications to develop mcl-PHAs further is challenging.

Corynebacterium glutamicum is used as an industrial platform organism for amino acid production. Previously, the organism was utilized to produce l-histidine with research focusing on metabolic engineering approaches to increase titer and yield. Only a few studies have been published that provide information on bioprocess development, with media optimization and fed-batch cultivation procedure being particularly promising areas. In this work, we show how experimental setups such as miniature cultivation technology, dynamic and time-optimized LC-MS/MS metabolic footprinting tools, and automated workflows for the detection of local and global metabolic patterns can significantly accelerate bioprocess development. Potential media bottlenecks in form of phosphate and magnesium availability were identified by sensitivity analysis in parallelized microscale cultivation assisted by lab automation. A rapid dilute-and-shoot flow-injection-analysis tandem mass spectrometry approach was used to cope with the resulting cultivation throughput and allowed to quantify amino acids with 1 min per sample. We were able to increase the l-histidine titer of a C. glutamicum random mutagenesis mutant by a factor of 5.8 through process optimization while also identifying both known and previously unknown targets for additional strain improvements. The presented methodology can be seen as a supplement to traditional approaches in the field of bioprocess development.