Protein design meets biosecurity.

The power and accuracy of computational protein design have been increasing rapidly with the incorporation of artificial intelligence (AI) approaches. This promises to transform biotechnology, enabling advances across sustainability and medicine. DNA synthesis plays a critical role in materializing designed proteins. However, as with all major revolutionary changes, this technology is vulnerable to misuse and the production of dangerous biological agents. To enable the full benefits of this revolution while mitigating risks that may emerge, all synthetic gene sequence and synthesis data should be collected and stored in repositories that are only queried in emergencies to ensure that protein design proceeds in a safe, secure, and trustworthy manner.

Barriers and Opportunities for Clinical Nutritionists in 13 Latin American Countries: A Qualitative Study.

A clinical nutritionist (CN) is a university-educated professional trained to perform preventive and recovery functions in the health of patients. The actions of these professionals, both worldwide and in Latin America, may face barriers and opportunities that require careful identification and examination. The main objective of this study is to identify the most important barriers and opportunities for the clinical nutritionist in 13 Latin American countries. A qualitative study was carried out; the initial phase involved conducting in-depth individual interviews with 89 informants, experienced CNs from 13 Latin American countries. After calculating the mean and standard deviation, we ranked the top 10 most frequently reported barriers by assigning a score ranging from 1 to 10. Additionally, 3 opportunities were identified with a lower score from 1 to 3. Means and standard deviation were calculated to sort the responses. Results: the most important barrier was the absence of public policies that regulate and/or monitor compliance with the staffing of CNs according to the number of hospital beds, while the most important opportunity was the advances in technology such as software, body analysis equipment and other tools used in Nutritional Care. The identified barriers can interfere with the professional performance of CNs and, moreover, make it difficult to monitor the good nutritional status of patients. It is recommended to consider the barriers identified in this study, as well as the opportunities, with a view to improving the quality of hospital services with an adequate supply of nutritionists.

Bacteriophages suppress CRISPR-Cas immunity using RNA-based anti-CRISPRs.

Many bacteria use CRISPR-Cas systems to combat mobile genetic elements, such as bacteriophages and plasmids1. In turn, these invasive elements have evolved anti-CRISPR proteins to block host immunity2,3. Here we unveil a distinct type of CRISPR-Cas Inhibition strategy that is based on small non-coding RNA anti-CRISPRs (Racrs). Racrs mimic the repeats found in CRISPR arrays and are encoded in viral genomes as solitary repeat units4. We show that a prophage-encoded Racr strongly inhibits the type I-F CRISPR-Cas system by interacting specifically with Cas6f and Cas7f, resulting in the formation of an aberrant Cas subcomplex. We identified Racr candidates for almost all CRISPR-Cas types encoded by a diverse range of viruses and plasmids, often in the genetic context of other anti-CRISPR genes5. Functional testing of nine candidates spanning the two CRISPR-Cas classes confirmed their strong immune inhibitory function. Our results demonstrate that molecular mimicry of CRISPR repeats is a widespread anti-CRISPR strategy, which opens the door to potential biotechnological applications6.

Evolution of a minimal cell.

Possessing only essential genes, a minimal cell can reveal mechanisms and processes that are critical for the persistence and stability of life1,2. Here we report on how an engineered minimal cell3,4 contends with the forces of evolution compared with the Mycoplasma mycoides non-minimal cell from which it was synthetically derived. Mutation rates were the highest among all reported bacteria, but were not affected by genome minimization. Genome streamlining was costly, leading to a decrease in fitness of greater than 50%, but this deficit was regained during 2,000 generations of evolution. Despite selection acting on distinct genetic targets, increases in the maximum growth rate of the synthetic cells were comparable. Moreover, when performance was assessed by relative fitness, the minimal cell evolved 39% faster than the non-minimal cell. The only apparent constraint involved the evolution of cell size. The size of the non-minimal cell increased by 80%, whereas the minimal cell remained the same. This pattern reflected epistatic effects of mutations in ftsZ, which encodes a tubulin-homologue protein that regulates cell division and morphology5,6. Our findings demonstrate that natural selection can rapidly increase the fitness of one of the simplest autonomously growing organisms. Understanding how species with small genomes overcome evolutionary challenges provides critical insights into the persistence of host-associated endosymbionts, the stability of streamlined chassis for biotechnology and the targeted refinement of synthetically engineered cells2,7-9.

Advancing our understanding of bioreactors for industrial-sized cell culture: health care and cellular agriculture implications.

Bioreactors are advanced biomanufacturing tools that have been widely used to develop various applications in the fields of health care and cellular agriculture. In recent years, there has been a growing interest in the use of bioreactors to enhance the efficiency and scalability of these technologies. In cell therapy, bioreactors have been used to expand and differentiate cells into specialized cell types that can be used for transplantation or tissue regeneration. In cultured meat production, bioreactors offer a controlled and efficient means of producing meat without the need for animal farming. Bioreactors can support the growth of muscle cells by providing the necessary conditions for cell proliferation, differentiation, and maturation, including the provision of oxygen and nutrients. This review article aims to provide an overview of the current state of bioreactor technology in both cell therapy and cultured meat production. It will examine the various bioreactor types and their applications in these fields, highlighting their advantages and limitations. In addition, it will explore the future prospects and challenges of bioreactor technology in these emerging fields. Overall, this review will provide valuable insights for researchers and practitioners interested in using bioreactor technology to develop innovative solutions in the biomanufacturing of therapeutic cells and cultured meat.

Versatility of mesenchymal stem cell-derived extracellular vesicles in tissue repair and regenerative applications.

Mesenchymal stem/stromal cells (MSCs) are multipotent somatic cells that have been widely explored in the field of regenerative medicine. MSCs possess the ability to secrete soluble factors as well as lipid bound extracellular vesicles (EVs). MSCs have gained increased interest and attention as a result of their therapeutic properties, which are thought to be attributed to their secretome. However, while the use of MSCs as whole cells pose heterogeneity concerns and survival issues post-transplantation, such limitations are absent in cell-free EV-based treatments. EVs derived from MSCs are promising therapeutic agents for a range of clinical conditions and disorders owing to their immunomodulatory, pro-regenerative, anti-inflammatory, and antifibrotic activity. Recent successes with preclinical studies using EVs for repair and regeneration of damaged tissues such as cardiac tissue, lung, liver, pancreas, bone, skin, cornea, and blood diseases are discussed in this review. We also discuss delivery strategies of EVs using biomaterials as delivery vehicles through systemic or local administration. Despite its effectiveness in preclinical investigations, the application of MSC-EV in clinical settings will necessitate careful consideration surrounding issues such as: i) scalability and isolation, ii) biodistribution, iii) targeting specific tissues, iv) quantification and characterization, and v) safety and efficacy of dosage. The future of EVs in regenerative medicine is promising yet still needs further investigation on enhancing the efficacy, scalability, and potency for clinical applications.

Cell-free enzyme cascades - application and transition from development to industrial implementation.

In the vision to realize a circular economy aiming for net carbon neutrality or even negativity, cell-free bioconversion of sustainable and renewable resources emerged as a promising strategy. The potential of in vitro systems is enormous, delivering technological, ecological, and ethical added values. Innovative concepts arose in cell-free enzymatic conversions to reduce process waste production and preserve fossil resources, as well as to redirect and assimilate released industrial pollutions back into the production cycle again. However, the great challenge in the near future will be the jump from a concept to an industrial application. The transition process in industrial implementation also requires economic aspects such as productivity, scalability, and cost-effectiveness. Here, we briefly review the latest proof-of-concept cascades using carbon dioxide and other C1 or lignocellulose-derived chemicals as blueprints to efficiently recycle greenhouse gases, as well as cutting-edge technologies to maturate these concepts to industrial pilot plants.

Aportes de la biotecnología en el diagnóstico de COVID-19 / Biotechnology contributions in COVID-19 diagnosis

Introducción: en diciembre del año 2019 surgió en China una neumonía viral; el virus fue identificado como un coronavirus SARS-CoV-2, que se propagó rápidamente de tal manera que se convirtió en pandemia. La alta contagiosidad y la presencia de portadores asintomáticos dificultaron el diagnóstico de la infección y la toma de decisiones sanitarias. Objetivo: el objetivo de esta revisión bibliográfica es presentar y describir las principales técnicas utilizadas actualmente para el diagnóstico de COVID-19 y establecer su relación con los conocimientos de distintas disciplinas y tecnologías emergentes que confluyen en la Biotecnología bioquímico-farmacéutica orientada a la Salud humana. Metodología: se realizó una revisión de la bibliografía disponible en PubMed a partir de enero de 2020 sobre las pruebas diagnósticas que se encuentran actualmente en uso, en el ámbito sanitario, para la detección y seguimiento de la enfermedad COVID-19. También se realizaron búsquedas a través de Google y Google Académico para publicaciones de organismos de Salud en referencia a métodos diagnósticos. Resultados: se presenta una importante cantidad de pruebas diagnósticas, basadas en diferentes tecnologías, que desempeñan un papel clave en la pandemia de COVID-19. Algunas de ellas muy sofisticadas, como la secuenciación genómica de próxima generación, otras más estándar, pero igualmente robustas, como la reacción en cadena de la polimerasa (PCR). También otras adaptadas para el brote pandémico, como la amplificación isotérmica de ácidos nucleicos mediada por bucle. Todas las mencionadas se consideran de tipo molecular, pero también existen las pruebas serológicas, como ELISA, que incluyen ensayos en plasma o de tipo inmunológico. Estas sirven para detectar anticuerpos frente a la exposición al virus o antígenos en personas potencialmente infectadas. Conclusiones: los procesos de investigación y desarrollo biotecnológicos aplicados al diagnóstico y los conocimientos científicos previos permitieron una respuesta tanto nacional como internacional rápida y eficaz en medio de una inédita pandemia global. En esta revisión destacamos las principales técnicas, en qué estadio se deben usar y qué información nos aportan. (AU)

Introduction: in December 2019, a viral pneumonia emerged in China, identifying the virus as a SARS-CoV-2 coronavirus, which spread rapidly in such a way that it became a pandemic. The high contagiousness and the presence of asymptomatic carriers make difficulted to diagnose the infection and to make health decisions. Target: the objective of this review is to present and describe the main techniques currently used for the diagnosis of COVID-19, and to establish their relationship with the knowledge of different disciplines and emerging technologies that converge in biochemical-pharmaceutical biotechnology oriented to human health. Methodology: a review of the literature available in Pubmed from January 2020 on the diagnostic tests that are currently in use in the health field, for the detection and monitoring of COVID-19 disease, was carried out. Searches were also carried out through Google and Google Scholar for publications of Health organizations in reference to diagnostic methods. Results: a significant number of diagnostic tests are presented, based on different technologies, which play a key role in the COVID-19 pandemic. Some of them are very sophisticated, such as next-generation genomic sequencing, others more standard, but equally robust, such as polymerase chain reaction. Also others adapted for the pandemic outbreak such as loop-mediated isothermal amplification of nucleic acids. All of the aforementioned are considered molecular, but there are also serological tests, such as ELISA, which include plasma or immunological tests. These serve to detect antibodies against exposure to the virus or antigens in potentially infected people. Conclusions: biotechnological research and development processes applied to diagnosis and previous scientific knowledge allowed a rapid and effective national and international response in the midst of an unprecedented global pandemic. In this review we highlight the main techniques, at what stage they should be used and what information they provide us. (AU)

Digital models in biotechnology: Towards multi-scale integration and implementation.

Industrial biotechnology encompasses a large area of multi-scale and multi-disciplinary research activities. With the recent megatrend of digitalization sweeping across all industries, there is an increased focus in the biotechnology industry on developing, integrating and applying digital models to improve all aspects of industrial biotechnology. Given the rapid development of this field, we systematically classify the state-of-art modelling concepts applied at different scales in industrial biotechnology and critically discuss their current usage, advantages and limitations. Further, we critically analyzed current strategies to couple cell models with computational fluid dynamics to study the performance of industrial microorganisms in large-scale bioprocesses, which is of crucial importance for the bio-based production industries. One of the most challenging aspects in this context is gathering intracellular data under industrially relevant conditions. Towards comprehensive models, we discuss how different scale-down concepts combined with appropriate analytical tools can capture intracellular states of single cells. We finally illustrated how the efforts could be used to develop digitals models suitable for both cell factory design and process optimization at industrial scales in the future.

Comparing in planta accumulation with microbial routes to set targets for a cost-competitive bioeconomy.

Plants and microbes share common metabolic pathways for producing a range of bioproducts that are potentially foundational to the future bioeconomy. However, in planta accumulation and microbial production of bioproducts have never been systematically compared on an economic basis to identify optimal routes of production. A detailed technoeconomic analysis of four exemplar compounds (4-hydroxybenzoic acid [4-HBA], catechol, muconic acid, and 2-pyrone-4,6-dicarboxylic acid [PDC]) is conducted with the highest reported yields and accumulation rates to identify economically advantaged platforms and breakeven targets for plants and microbes. The results indicate that in planta mass accumulation ranging from 0.1 to 0.3 dry weight % (dwt%) can achieve costs comparable to microbial routes operating at 40 to 55% of maximum theoretical yields. These yields and accumulation rates are sufficient to be cost competitive if the products are sold at market prices consistent with specialty chemicals ($20 to $50/kg). Prices consistent with commodity chemicals will require an order-of-magnitude-greater accumulation rate for plants and/or yields nearing theoretical maxima for microbial production platforms. This comparative analysis revealed that the demonstrated accumulation rates of 4-HBA (3.2 dwt%) and PDC (3.0 dwt%) in engineered plants vastly outperform microbial routes, even if microbial platforms were to reach theoretical maximum yields. Their recovery and sale as part of a lignocellulosic biorefinery could enable biofuel prices to be competitive with petroleum. Muconic acid and catechol, in contrast, are currently more attractive when produced microbially using a sugar feedstock. Ultimately, both platforms can play an important role in replacing fossil-derived products.

The road to fully programmable protein catalysis.

The ability to design efficient enzymes from scratch would have a profound effect on chemistry, biotechnology and medicine. Rapid progress in protein engineering over the past decade makes us optimistic that this ambition is within reach. The development of artificial enzymes containing metal cofactors and noncanonical organocatalytic groups shows how protein structure can be optimized to harness the reactivity of nonproteinogenic elements. In parallel, computational methods have been used to design protein catalysts for diverse reactions on the basis of fundamental principles of transition state stabilization. Although the activities of designed catalysts have been quite low, extensive laboratory evolution has been used to generate efficient enzymes. Structural analysis of these systems has revealed the high degree of precision that will be needed to design catalysts with greater activity. To this end, emerging protein design methods, including deep learning, hold particular promise for improving model accuracy. Here we take stock of key developments in the field and highlight new opportunities for innovation that should allow us to transition beyond the current state of the art and enable the robust design of biocatalysts to address societal needs.