Structure and Topology Prediction of Phage Adhesion Devices Using AlphaFold2: The Case of Two Oenococcus oeni Phages

Isolation and structure elucidation of cell surface polysaccharides from Oenococcus oeni

The Gram-positive bacterium Oenococcus oeni is a major player in wine malolactic fermentation. In O. oeni, cell wall polysaccharides are considered putative receptors for bacteriophages, virus predators that lead to fermentation failures. In this study, we have developed an efficient stepwise extraction protocol to extract polysaccharides from the cell wall of O. oeni IOEBS277, which were analyzed by methylation, 1D, 2D-NMR spectroscopy, and MALDI-QIT-TOF mass spectrometry. The chemical structures of the two major purified polysaccharides were elucidated. The first one is a heteropolysaccharide with repeating units consisting of a branched hexasaccharide and one glycerol residue, linked by phosphodiester bonds. The second one consists of a →6)-β-Galf-(1→ galactofuranan chain partially substituted on the C-2 hydroxyl with β-Glcp. HR-MAS NMR analysis of intact O. oeni cells indicated that both polysaccharides are exposed to the bacterial surface.

Advancements in protein structure prediction: A comparative overview of AlphaFold and its derivatives

This review provides a comprehensive analysis of AlphaFold (AF) and its derivatives (AF2 and AF3) in protein structure prediction. These tools have revolutionized structural biology with their highly accurate predictions, driving progress in protein modeling, drug discovery, and the study of protein dynamics. Its exceptional accuracy has redefined our understanding of protein folding, which enables groundbreaking advancements in protein design, disease research and discusses future integration with experimental techniques. In addition, their achievement features, architectures, important case studies, and noteworthy effects in the field of biology and medicine were evaluated. In consideration of the fact that AF2 is a relatively recent innovation, it has already been taken into account in many studies that highlight its applications in many ways. Moreover, the limitations of AF2 that directed to the introduction of AF3 are also reported, which is a great improvement as it provides precise predictions of the structures and interactions of proteins, DNA, RNA, and ligands, thereby aiding in the understanding of the molecular level. Addressing current challenges and forecasting future developments, this work underscores the lasting significance of AF in reshaping the scientific landscape of protein research.

Multi-Epitopic Peptide Vaccine Against Newcastle Disease Virus: Molecular Dynamics Simulation and Experimental Validation

BACKGROUND

Newcastle disease virus (NDV) is a highly contagious and economically devastating pathogen affecting poultry worldwide, leading to significant losses in the poultry industry. Despite existing vaccines, outbreaks continue to occur, highlighting the need for more effective vaccination strategies. Developing a multi-epitopic peptide vaccine offers a promising approach to enhance protection against NDV.

OBJECTIVES

Here, we aimed to design and evaluate a multi-epitopic vaccine against NDV using molecular dynamics (MD) simulation.

METHODOLOGY

We retrieved NDV sequences for the fusion (F) protein and hemagglutinin-neuraminidase (HN) protein. Subsequently, B-cell and T-cell epitopes were predicted. The top potential epitopes were utilized to design the vaccine construct, which was subsequently docked against chicken TLR4 and MHC1 receptors to assess the immunological response. The resulting docked complex underwent a 1 microsecond (1000 ns) MD simulation. For experimental evaluation, the vaccine's efficacy was assessed in mice and chickens using a controlled study design, where animals were randomly divided into groups receiving either a local ND vaccine or the peptide vaccine or a control treatment.

RESULTS

The 40 amino acid peptide vaccine demonstrated strong binding affinity and stability within the TLR4 and MHC1 receptor-peptide complexes. The root mean square deviation of peptide vaccine and TLR4 receptor showed rapid stabilization after an initial repositioning. The root mean square fluctuation revealed relatively low fluctuations (below 3 Å) for the TLR4 receptor, while the peptide exhibited higher fluctuations. The overall binding energy of the peptide vaccine with TLR4 and MHC1 receptors amounted to -15.7 kcal·mol-1 and -36.8 kcal·mol-1, respectively. For experimental evaluations in mice and chicken, the peptide vaccine was synthesized using services of GeneScript Biotech® (Singapore) PTE Limited. Experimental evaluations showed a significant immune response in both mice and chickens, with the vaccine eliciting robust antibody production, as evidenced by increasing HI titers over time. Statistical analysis was performed using an independent t-test with Type-II error to compare the groups, calculating the p-values to determine the significance of the immune response between different groups.

CONCLUSIONS

Multi-epitopic peptide vaccine has demonstrated a good immunological response in natural hosts.

AlphaFold2 in biomedical research: facilitating the development of diagnostic strategies for disease

Proteins, as the primary executors of physiological activity, serve as a key factor in disease diagnosis and treatment. Research into their structures, functions, and interactions is essential to better understand disease mechanisms and potential therapies. DeepMind's AlphaFold2, a deep-learning protein structure prediction model, has proven to be remarkably accurate, and it is widely employed in various aspects of diagnostic research, such as the study of disease biomarkers, microorganism pathogenicity, antigen-antibody structures, and missense mutations. Thus, AlphaFold2 serves as an exceptional tool to bridge fundamental protein research with breakthroughs in disease diagnosis, developments in diagnostic strategies, and the design of novel therapeutic approaches and enhancements in precision medicine. This review outlines the architecture, highlights, and limitations of AlphaFold2, placing particular emphasis on its applications within diagnostic research grounded in disciplines such as immunology, biochemistry, molecular biology, and microbiology.

Biological and bioinformatic tools for the discovery of unknown phage-host combinations

The field of microbial ecology has been transformed by metagenomics in recent decades and has culminated in vast datasets that facilitate the bioinformatic dissection of complex microbial communities. Recently, attention has turned from defining the microbiota composition to the interactions and relationships that occur between members of the microbiota. Within complex microbiota, the identification of bacteriophage-host combinations has been a major challenge. Recent developments in artificial intelligence tools to predict protein structure and function as well as the relationships between bacteria and their infecting bacteriophages allow a strategic approach to identifying and validating phage-host relationships. However, biological validation of these predictions remains essential and will serve to improve the existing predictive tools. In this review, I provide an overview of the most recent developments in both bioinformatic and experimental approaches to predicting and experimentally validating unknown phage-host combinations.

Molecular origin and biological effects of exercise mimetics

With the rapid development of sports science and molecular biology technology, academia refers to molecules or microorganisms that mimic or enhance the beneficial effects of exercise on the body, called "exercise mimetics." This review aims to clarify the concept and development history of exercise mimetics, and to define the concept of exercise mimetics by summarizing its characteristics and functions. Candidate molecules and drug targets for exercise mimetics are summarized, and the relationship between exercise mimetics and exercise is explained, as well as the targeting system and function of exercise mimetics. The main targeting systems for exercise mimetics are the exercise system, circulatory system, endocrine system, endocrine system, and nervous system, while the immune system is potential targeting systems. Finally, future research directions for exercise mimetics are discussed.

Identification of Two Flip-Over Genes in Grass Family as Potential Signature of C4 Photosynthesis Evolution

In flowering plants, C4 photosynthesis is superior to C3 type in carbon fixation efficiency and adaptation to extreme environmental conditions, but the mechanisms behind the assembly of C4 machinery remain elusive. This study attempts to dissect the evolutionary divergence from C3 to C4 photosynthesis in five photosynthetic model plants from the grass family, using a combined comparative transcriptomics and deep learning technology. By examining and comparing gene expression levels in bundle sheath and mesophyll cells of five model plants, we identified 16 differentially expressed signature genes showing cell-specific expression patterns in C3 and C4 plants. Among them, two showed distinctively opposite cell-specific expression patterns in C3 vs. C4 plants (named as FOGs). The in silico physicochemical analysis of the two FOGs illustrated that C3 homologous proteins of LHCA6 had low and stable pI values of ~6, while the pI values of LHCA6 homologs increased drastically in C4 plants Setaria viridis (7), Zea mays (8), and Sorghum bicolor (over 9), suggesting this protein may have different functions in C3 and C4 plants. Interestingly, based on pairwise protein sequence/structure similarities between each homologous FOG protein, one FOG PGRL1A showed local inconsistency between sequence similarity and structure similarity. To find more examples of the evolutionary characteristics of FOG proteins, we investigated the protein sequence/structure similarities of other FOGs (transcription factors) and found that FOG proteins have diversified incompatibility between sequence and structure similarities during grass family evolution. This raised an interesting question as to whether the sequence similarity is related to structure similarity during C4 photosynthesis evolution.

Insights into the Alcyoneusvirus Adsorption Complex

The structures of the Caudovirales phage tails are key factors in determining the host specificity of these viruses. However, because of the enormous structural diversity, the molecular anatomy of the host recognition apparatus has been elucidated in only a number of phages. Klebsiella viruses vB_KleM_RaK2 (RaK2) and phiK64-1, which form a new genus Alcyoneusvirus according to the ICTV, have perhaps one of the most structurally sophisticated adsorption complexes of all tailed viruses described to date. Here, to gain insight into the early steps of the alcyoneusvirus infection process, the adsorption apparatus of bacteriophage RaK2 is studied in silico and in vitro. We experimentally demonstrate that ten proteins, gp098 and gp526-gp534, previously designated as putative structural/tail fiber proteins (TFPs), are present in the adsorption complex of RaK2. We show that two of these proteins, gp098 and gp531, are essential for attaching to Klebsiella pneumoniae KV-3 cells: gp531 is an active depolymerase that recognizes and degrades the capsule of this particular host, while gp098 is a secondary receptor-binding protein that requires the coordinated action of gp531. Finally, we demonstrate that RaK2 long tail fibers consist of nine TFPs, seven of which are depolymerases, and propose a model for their assembly.

Using AlphaFold Predictions in Viral Research

Elucidation of the tertiary structure of proteins is an important task for biological and medical studies. AlphaFold, a modern deep-learning algorithm, enables the prediction of protein structure to a high level of accuracy. It has been applied in numerous studies in various areas of biology and medicine. Viruses are biological entities infecting eukaryotic and procaryotic organisms. They can pose a danger for humans and economically significant animals and plants, but they can also be useful for biological control, suppressing populations of pests and pathogens. AlphaFold can be used for studies of molecular mechanisms of viral infection to facilitate several activities, including drug design. Computational prediction and analysis of the structure of bacteriophage receptor-binding proteins can contribute to more efficient phage therapy. In addition, AlphaFold predictions can be used for the discovery of enzymes of bacteriophage origin that are able to degrade the cell wall of bacterial pathogens. The use of AlphaFold can assist fundamental viral research, including evolutionary studies. The ongoing development and improvement of AlphaFold can ensure that its contribution to the study of viral proteins will be significant in the future.

Novel machine learning approaches revolutionize protein knowledge

Breakthrough methods in machine learning (ML), protein structure prediction, and novel ultrafast structural aligners are revolutionizing structural biology. Obtaining accurate models of proteins and annotating their functions on a large scale is no longer limited by time and resources. The most recent method to be top ranked by the Critical Assessment of Structure Prediction (CASP) assessment, AlphaFold 2 (AF2), is capable of building structural models with an accuracy comparable to that of experimental structures. Annotations of 3D models are keeping pace with the deposition of the structures due to advancements in protein language models (pLMs) and structural aligners that help validate these transferred annotations. In this review we describe how recent developments in ML for protein science are making large-scale structural bioinformatics available to the general scientific community.

Exploring Host-Binding Machineries of Mycobacteriophages with AlphaFold2

Although more than 12,000 bacteriophages infecting mycobacteria (mycobacteriophages) have been isolated so far, there is a knowledge gap on their structure-function relationships. Here, we have explored the architecture of host-binding machineries from seven representative mycobacteriophages of the Siphoviridae family infecting Mycobacterium smegmatis, Mycobacterium abscessus, and Mycobacterium tuberculosis, using AlphaFold2 (AF2). AF2 enables confident structural analyses of large and flexible biological assemblies resistant to experimental methods, thereby opening new avenues to shed light on phage structure and function. Our results highlight the modularity and structural diversity of siphophage host-binding machineries that recognize host-specific receptors at the onset of viral infection. Interestingly, the studied mycobacteriophages' host-binding machineries present unique features compared with those of phages infecting other Gram-positive actinobacteria. Although they all assemble the classical Dit (distal tail), Tal (tail-associated lysin), and receptor-binding proteins, five of them contain two potential additional adhesion proteins. Moreover, we have identified brush-like domains formed of multiple polyglycine helices which expose hydrophobic residues as potential receptor-binding domains. These polyglycine-rich domains, which have been observed in only five native proteins, may be a hallmark of mycobacteriophages' host-binding machineries, and they may be more common in nature than expected. Altogether, the unique composition of mycobacteriophages' host-binding machineries indicate they might have evolved to bind to the peculiar mycobacterial cell envelope, which is rich in polysaccharides and mycolic acids. This work provides a rational framework to efficiently produce recombinant proteins or protein domains and test their host-binding function and, hence, to shed light on molecular mechanisms used by mycobacteriophages to infect their host. IMPORTANCE Mycobacteria include both saprophytes, such as the model system Mycobacterium smegmatis, and pathogens, such as Mycobacterium tuberculosis and Mycobacterium abscessus, that are poorly responsive to antibiotic treatments and pose a global public health problem. Mycobacteriophages have been collected at a very large scale over the last decade, and they have proven to be valuable tools for mycobacteria genetic manipulation, rapid diagnostics, and infection treatment. Yet, molecular mechanisms used by mycobacteriophages to infect their host remain poorly understood. Therefore, exploring the structural diversity of mycobacteriophages' host-binding machineries is important not only to better understand viral diversity and bacteriophage-host interactions, but also to rationally develop biotechnological tools. With the powerful protein structure prediction software AlphaFold2, which was publicly released a year ago, it is now possible to gain structural and functional insights on such challenging assemblies.

A perfect fit: Bacteriophage receptor-binding proteins for diagnostic and therapeutic applications

Bacteriophages are the most abundant biological entity on earth, acting as the predators and evolutionary drivers of bacteria. Owing to their inherent ability to specifically infect and kill bacteria, phages and their encoded endolysins and receptor-binding proteins (RBPs) have enormous potential for development into precision antimicrobials for treatment of bacterial infections and microbial disbalances; or as biocontrol agents to tackle bacterial contaminations during various biotechnological processes. The extraordinary binding specificity of phages and RBPs can be exploited in various areas of bacterial diagnostics and monitoring, from food production to health care. We review and describe the distinctive features of phage RBPs, explain why they are attractive candidates for use as therapeutics and in diagnostics, discuss recent applications using RBPs, and finally provide our perspective on how synthetic technology and artificial intelligence-driven approaches will revolutionize how we use these tools in the future.

Characterization of Klebsiella pneumoniae bacteriophages, KP1 and KP12, with deep learning-based structure prediction

Concerns over Klebsiella pneumoniae resistance to the last-line antibiotic treatment have prompted a reconsideration of bacteriophage therapy in public health. Biotechnological application of phages and their gene products as an alternative to antibiotics necessitates the understanding of their genomic context. This study sequenced, annotated, characterized, and compared two Klebsiella phages, KP1 and KP12. Physiological validations identified KP1 and KP12 as members of Myoviridae family. Both phages showed that their activities were stable in a wide range of pH and temperature. They exhibit a host specificity toward K. pneumoniae with a broad intraspecies host range. General features of genome size, coding density, percentage GC content, and phylogenetic analyses revealed that these bacteriophages are distantly related. Phage lytic proteins (endolysin, anti-/holin, spanin) identified by the local alignment against different databases, were subjected to further bioinformatic analyses including three-dimensional (3D) structure prediction by AlphaFold. AlphaFold models of phage lysis proteins were consistent with the published X-ray crystal structures, suggesting the presence of T4-like and P1/P2-like bacteriophage lysis proteins in KP1 and KP12, respectively. By providing the primary sequence information, this study contributes novel bacteriophages for research and development pipelines of phage therapy that ultimately, cater to the unmet clinical and industrial needs against K. pneumoniae pathogens.

Phage Adsorption to Gram-Positive Bacteria

The phage life cycle is a multi-stage process initiated by the recognition and attachment of the virus to its bacterial host. This adsorption step depends on the specific interaction between bacterial structures acting as receptors and viral proteins called Receptor Binding Proteins (RBP). The adsorption process is essential as it is the first determinant of phage host range and a sine qua non condition for the subsequent conduct of the life cycle. In phages belonging to the Caudoviricetes class, the capsid is attached to a tail, which is the central player in the adsorption as it comprises the RBP and accessory proteins facilitating phage binding and cell wall penetration prior to genome injection. The nature of the viral proteins involved in host adhesion not only depends on the phage morphology (i.e., myovirus, siphovirus, or podovirus) but also the targeted host. Here, we give an overview of the adsorption process and compile the available information on the type of receptors that can be recognized and the viral proteins taking part in the process, with the primary focus on phages infecting Gram-positive bacteria.

Exploring Structural Diversity among Adhesion Devices Encoded by Lactococcal P335 Phages with AlphaFold2

Bacteriophages, or phages, are the most abundant biological entities on Earth. They possess molecular nanodevices to package and store their genome, as well as to introduce it into the cytoplasm of their bacterial prey. Successful phage infection commences with specific recognition of, and adhesion to, a suitable host cell surface. Adhesion devices of siphophages infecting Gram-positive bacteria are very diverse and remain, for the majority, poorly understood. These assemblies often comprise long, flexible, and multi-domain proteins, which limit their structural analyses by experimental approaches. The protein structure prediction program AlphaFold2 is exquisitely adapted to unveil structural and functional details of such molecular machineries. Here, we present structure predictions of adhesion devices from siphophages belonging to the P335 group infecting Lactococcus spp., one of the most extensively applied lactic acid bacteria in dairy fermentations. The predictions of representative adhesion devices from types I-IV P335 phages illustrate their very diverse topology. Adhesion devices from types III and IV phages share a common topology with that of Skunavirus p2, with a receptor binding protein anchored to the virion by a distal tail protein loop. This suggests that they exhibit an activation mechanism similar to that of phage p2 prior to host binding.

Improving the Product Specificity of Maltotetraose-Forming Amylase from Pseudomonas saccharophila STB07 by Removing the Carbohydrate-Binding Module

Maltotetraose (G4) is composed of four glucose units linked by the α-1,4-glycosidic bond, which has excellent adaptability in food processing and specific physiological functions. Maltotetraose-forming amylases (MFAses) are used in the industry as a promising tool for G4 production. The MFAse from Pseudomonas saccharophila STB07 (MFA_PS), which belongs to the GH13, can preferentially hydrolyze substrates to G4. MFA_PS contains a carbohydrate-binding module (CBM). In this study, we removed the CBM to obtain the mutant MFA_PS-ΔCBM. We explored the aspects affecting the catalytic performance of enzymes through structural simulations and molecular docking. Results showed that when the CBM was removed, the thermal stability of MFA_PS was slightly reduced, and its catalytic ability for long-chain substrates, such as corn starch, was significantly reduced. However, the catalytic ability and product specificity of the substrates with shorter chain length, such as maltodextrin (DE 7-9), were improved. The G1-G7 (glucose (G1), maltose (G2), maltotriose (G3), maltotetraose (G4), maltopentaose (G5), maltohexaose (G6), and maltoheptaose (G7)) contents and G4 proportion of the mutant MFA_PS-ΔCBM reaction at 24 h were 11.1 and 11.6% higher than those of MFA_PS, respectively. The results also showed that the forces of MFA_PS on the substrate near the -4, -1, +1, and +3 subsites were critical for its product specificity.

Phage-host interactions as a driver of population dynamics during wine fermentation: Betting on underdogs

Winemaking is a complex process in which numerous microorganisms, mainly yeasts and lactic acid bacteria (LAB), play important roles. After alcoholic fermentation (AF), most wines undergo malolactic fermentation (MLF) to improve their organoleptic properties and microbiological stability. Oenococcus oeni is mainly responsible for this crucial process where L-malic acid (MA) in wine converts to softer L-lactic acid. The bacterium is better adapted to the limiting conditions imposed by the wine matrix and performs MLF under regular winemaking conditions, especially in wines with a pH below 3.5. Traditionally, this process has been conducted by the natural microbiota present within the winery. However, the start, duration and qualitative impact of spontaneous MLF are unpredictable, which prompts winemakers to use pure starter cultures of selected bacteria to promote a more reliable, simple, fast and efficient fermentation. Yet, their use does not always ensure a problem-free fermentation. Spontaneous initiation of the process may prove very difficult or does not occur at all. Such difficulties arise from a combination of factors found in some wines upon the completion of AF (high ethanol concentration, low temperature and pH, low nutrient concentrations, presence of free and bound SO₂). Alongside these well documented facts, research has also provided evidence that negative interactions between O. oeni and other biological entities such as yeasts may also impact MLF. Another insufficiently described, but highly significant factor inhibiting bacterial growth is connected to the presence of bacteriophages of O. oeni which are frequently associated to musts and wines. The purpose of this review is to summarize the current knowledge about the phage life cycles and possible impacts on the trajectory of the microbiota during winemaking.

A structural discovery journey of streptococcal phages adhesion devices by AlphaFold2

Successful bacteriophage infection starts with specific recognition and adhesion to the host cell surface. Adhesion devices of siphophages infecting Gram-positive bacteria are very diverse and remain, for the majority, poorly understood. These assemblies often comprise long, flexible, and multi-domain proteins, which limits their structural analyses by experimental approaches such as X-ray crystallography and electron microscopy. However, the protein structure prediction program AlphaFold2 is exquisitely adapted to unveil structural and functional details of such molecular machineries. Here, we present structure predictions of whole adhesion devices of five representative siphophages infecting Streptococcus thermophilus, one of the main lactic acid bacteria used in dairy fermentations. The predictions highlight the mosaic nature of these devices that share functional domains for which active sites and residues could be unambiguously identified. Such AlphaFold2 analyses of phage-encoded host adhesion devices should become a standard method to characterize phage-host interaction machineries and to reliably annotate phage genomes.

Structure Prediction and Analysis of Hepatitis E Virus Non-Structural Proteins from the Replication and Transcription Machinery by AlphaFold2

Hepatitis E virus (HEV) is a major cause of acute viral hepatitis in humans globally. Considered for a long while a public health issue only in developing countries, the HEV infection is now a global public health concern. Most human infections are caused by the HEV genotypes 1, 2, 3 and 4 (HEV-1 to HEV-4). Although HEV-3 and HEV-4 can evolve to chronicity in immunocompromised patients, HEV-1 and HEV-2 lead to self-limited infections. HEV has a positive-sense single-stranded RNA genome of ~7.2 kb that is translated into a large pORF1 replicative polyprotein, essential for the viral RNA genome replication and transcription. Unfortunately, the composition and structure of these replicases are still unknown. The recent release of the powerful machine-learning protein structure prediction software AlphaFold2 (AF2) allows us to accurately predict the structure of proteins and their complexes. Here, we used AF2 with the replicase encoded by the polyprotein pORF1 of the human-infecting HEV-3. The boundaries and structures reveal five domains or nonstructural proteins (nsPs): the methyltransferase, Zn-binding domain, macro, helicase, and RNA-dependent RNA polymerase, reliably predicted. Their substrate-binding sites are similar to those observed experimentally for other related viral proteins. Precisely knowing enzyme boundaries and structures is highly valuable to recombinantly produce stable and active proteins and perform structural, functional and inhibition studies.

Present Impact of AlphaFold2 Revolution on Structural Biology, and an Illustration With the Structure Prediction of the Bacteriophage J-1 Host Adhesion Device

In 2021, the release of AlphaFold2 - the DeepMind's machine-learning protein structure prediction program - revolutionized structural biology. Results of the CASP14 contest were an immense surprise as AlphaFold2 successfully predicted 3D structures of nearly all submitted protein sequences. The AlphaFold2 craze has rapidly spread the life science community since structural biologists as well as untrained biologists have now the possibility to obtain high-confidence protein structures. This revolution is opening new avenues to address challenging biological questions. Moreover, AlphaFold2 is imposing itself as an essential step of any structural biology project, and requires us to revisit our structural biology workflows. On one hand, AlphaFold2 synergizes with experimental methods including X-ray crystallography and cryo-electron microscopy. On the other hand, it is, to date, the only method enabling structural analyses of large and flexible assemblies resistant to experimental approaches. We illustrate this valuable application of AlphaFold2 with the structure prediction of the whole host adhesion device from the Lactobacillus casei bacteriophage J-1. With the ongoing improvement of AlphaFold2 algorithms and notebooks, there is no doubt that AlphaFold2-driven biological stories will increasingly be reported, which questions the future directions of experimental structural biology.

Disulfide Bond Engineering for Enhancing the Thermostability of the Maltotetraose-Forming Amylase from Pseudomonas saccharophila STB07

Maltooligosaccharides are a novel type of functional oligosaccharides with potential applications in food processing and can be produced by glycosyl hydrolases hydrolyzing starch. However, the main obstacle in industrial applications is the balance between the high temperature of the process and the stability of enzymes. In this study, based on the structural information and in silico tools (DSDBASE-MODIP, Disulfide by Design2 and FoldX), two disulfide bond mutants (A211C-S214C and S409C-Q412C) of maltotetraose-forming amylase from Pseudomonas saccharophila STB07 (MFA_ps) were generated to improve its thermostability. The mutation A211C-S214C was closer to the catalytic center and showed significantly improved thermostability with a 2.6-fold improved half-life at 60 °C and the thermal transition mid-point increased by 1.6 °C, compared to the wild-type. However, the thermostability of mutant S409C-Q412C, whose mutation sites are closely to CBM20, did not change observably. Molecular dynamics simulations revealed that both disulfide bonds A211C-S214C and S409C-Q412C rigidified the overall structure of MFA_ps, however, the impact on thermostability depends on the position and distance from the catalytic center.

Needle in a Whey-Stack: PhRACS as a Discovery Tool for Unknown Phage-Host Combinations

The field of metagenomics has rapidly expanded to become the go-to method for complex microbial community analyses. However, there is currently no straightforward route from metagenomics to traditional culture-based methods of strain isolation, particularly in (bacterio)phage biology, leading to an investigative bottleneck. Here, we describe a method that exploits specific phage receptor binding protein (RBP)-host cell surface receptor interaction enabling isolation of phage-host combinations from an environmental sample. The method was successfully applied to two complex sample types-a dairy-derived whey sample and an infant fecal sample, enabling retrieval of specific and culturable phage hosts. IMPORTANCE PhRACS aims to bridge the current divide between in silico genetic analyses (i.e., phageomic studies) and traditional culture-based methodology. Through the labeling of specific bacterial hosts with fluorescently tagged recombinant phage receptor binding proteins and the isolation of tagged cells using flow cytometry, PhRACS allows the full potential of phageomic data to be realized in the wet laboratory.