Domain Sequences Research Articles

Functional Characterization of FgAsp, a Gene Coding an Aspartic Acid Protease in Fusarium graminearum

Aspartic proteases (APs), hydrolases with aspartic acid residues as catalytic active sites, are closely associated with processes such as plant growth and development and fungal and bacterial pathogenesis. F. graminearum is the dominant pathogenic fungus that causes Fusarium head blight (FHB) in wheat. However, the relationship of APs to the growth, development, and pathogenesis of F. graminearum is not clear. Therefore, we selected the FGSG_09558 gene, whose function annotation is aspartate protease, for further study. In this study, FGSG_09558 was found to contain a conserved structural domain and signal peptide sequence of aspartic acid protease and was therefore named FgAsp. The function of FgAsp in F. graminearum was investigated by constructing the knockout and complementation mutants of this gene. The results showed that with respect to the wild type (PH-1), the knockout mutant showed a significant reduction in mycelial growth, asexual spore production, and sexual spore formation, highlighting the key role of FgAsp in the growth and development of F. graminearum. In addition, the mutants showed a significant reduction in the virulence and accumulation level of deoxynivalenol (DON) content on maize whiskers, wheat germ sheaths, and wheat ears. DON, as a key factor of virulence, plays an important role in the F. graminearum infection of wheat ears, suggesting that FgAsp is involved in the regulation of F. graminearum pathogenicity by affecting the accumulation of the DON toxin. FgAsp had a significant effect on the ability of F. graminearum to utilize various sugars, especially arabinose. In response to the stress, hydrogen peroxide inhibited the growth of the mutant most significantly, indicating the important function of FgAsp in the strain’s response to environmental stress. Finally, FgAsp plays a key role in the regulation of F. graminearum growth and development, pathogenicity, and environmental stress response.

An Evaluation of the Cellular and Humoral Response of a Multi-Epitope Vaccine Candidate Against COVID-19 with Different Alum Adjuvants

SARS-CoV-2 (Betacoronavirus pandemicum) is responsible for the disease identified by the World Health Organization (WHO) as COVID-19. We designed “CHIVAX 2.1”, a multi-epitope vaccine, containing ten immunogenic peptides with conserved B-cell and T-cell epitopes in the receceptor binding domain (RBD) sequences of different SARS-CoV-2 variants of concern (VoCs). We evaluated the immune response of mice immunized with 20 or 60 µg of the chimeric protein with two different alum adjuvants (Alhydrogel® and Adju-Phos®), plus PHAD®, in a two-immunization regimen (0 and 21 days). Serum samples were collected on days 0, 21, 31, and 72 post first immunization, with antibody titers determined by indirect ELISA, while lymphoproliferation assays and cytokine production were evaluated by flow cytometry. The presence of neutralizing antibodies was assessed by surrogate neutralization assays. Higher titers of total IgG, IgG1, and IgG2a antibodies, as well as increased proliferation rates of specific CD4+ and CD8+ T cells, were observed in mice immunized with 60 μg of protein plus Adju-Phos®/PHAD®. This formulation also generated the highest levels of TNF-α and IFN-γ, in addition to the presence of neutralizing antibodies against Delta and Omicron VoC. These findings indicate the potential of this chimeric multi-epitope vaccine with combined adjuvants as a promising platform against viral infections, eliciting a TH1 or TH1:TH2 balanced cell response.

Exploring the biosynthesis potential of permafrost microbiomes

BackgroundPermafrost microbiomes are of paramount importance for the biogeochemistry of high latitude soils and while endemic biosynthetic domain sequences involved in secondary metabolism have been found in polar surface soils, the biosynthetic potential of permafrost microbiomes remains unexplored. Moreover, the nature of these ecosystems facilitates the unique opportunity to study the distribution and diversity of biosynthetic genes in relic DNA from ancient microbiomes. To explore the biosynthesis potential in permafrost, we used adenylation (AD) domain sequencing to evaluate non-ribosomal peptide (NRP) production in permafrost cores housing microbiomes separated at kilometer and kiloyear scales.ResultsPermafrost microbiomes represented NRP repertoires significantly different from that of temperate soil microbiomes, but as for temperate soils, the estimated domain richness and diversity was strongly correlated to the bacterial taxonomic diversity across locations. Furthermore, we found significant differences in both community composition and AD domain composition across geographical and temporal distances. Overall, the vast majority of biosynthetic domains showed below 90% amino acid similarity to characterized BGCs, confirming the high degree of novelty of NRPs inherent to permafrost microbiomes. Using available metagenomic sequences, we further identified a high biosynthetic diversity beyond NRPs throughout arctic surface soils down to deep and ancient (megayear old) permafrost microbiomes.ConclusionWe have shown that arctic permafrost microbiomes harbor a unique biosynthetic repertoire rich in hitherto undescribed NRPs. This diversity is driven by geographic separation across kilometer scales and by the bacterial taxonomic diversity between microbiomes confined in separate permafrost layers. Hence the permafrost biome represents a unique resource for studying secondary metabolism, and potentially for the discovery of novel drug leads.

Comparison of the activity of two elastin-like recombinant carriers fused to the antimicrobial peptide indolicidin

Recombinant fusion biotechnology is a powerful tool for producing antimicrobial peptides (AMPs), which can contribute to limiting the number of potentially infectious microorganisms. AMPs are often expressed in fusion with a carrier protein, a strategy that prevents toxic effects on host bacterial cells and protects them from proteolytic degradation. Among the many fusion carriers available, elastin-like polypeptides offer several valuable advantages related to their unique thermo-responsive behavior. The Human Elastin-like Polypeptide was successfully employed to produce a model fusion construct with the indolicidin domain. Recently, an elastin-based variant of this polypeptide was developed, modulating the sequence of the hydrophobic domains, thus enhancing the phase transition properties. Here, a new carrier based on this sequence that was produced, physicochemically characterized, and employed as a fusion partner for the indolicidin is described. This work aims to compare two different elastin-based carriers and their indolicidin fusion derivatives, as well as to determine, based on their properties, which may be the most advantageous carrier for producing antimicrobial domains. This study was focused on the elastin-like polypeptides as a tunable expression platform particularly suitable for producing AMPs and for their integration in biomimetic interfaces that acquire the capacity to inhibit bacterial growth.

Enhanced prediction of protein functional identity through the integration of sequence and structural features

Although over 300 million protein sequences are registered in a reference sequence database, only 0.2 % have experimentally determined functions. This suggests that many valuable proteins, potentially catalyzing novel enzymatic reactions, remain undiscovered among the vast number of function-unknown proteins. In this study, we developed a method to predict whether two proteins catalyze the same enzymatic reaction by analyzing sequence and structural similarities, utilizing structural models predicted by AlphaFold2. We performed pocket detection and domain decomposition for each structural model. The similarity between protein pairs was assessed using features such as full-length sequence similarity, domain structural similarity, and pocket similarity. We developed several models using conventional machine learning algorithms and found that the LightGBM-based model outperformed the models. Our method also surpassed existing approaches, including those based solely on full-length sequence similarity and state-of-the-art deep learning models. Feature importance analysis revealed that domain sequence identity, calculated through structural alignment, had the greatest influence on the prediction. Therefore, our findings demonstrate that integrating sequence and structural information improves the accuracy of protein function prediction.

Synthetic translational coupling element for multiplexed signal processing and cellular control.

Repurposing natural systems to develop customized functions in biological systems is one of the main thrusts of synthetic biology. Translational coupling is a common phenomenon in diverse polycistronic operons for efficient allocation of limited genetic space and cellular resources. These beneficial features of translation coupling can provide exciting opportunities for creating novel synthetic biological devices. Here, we introduce a modular synthetic translational coupling element (synTCE) and integrate this design with de novo designed riboregulators,toehold switches. A systematic exploration of sequence domain variants for synTCEs led to the identification of critical design considerations for improving the system performance. Next, this design approach was seamlessly integrated into logic computations and applied to construct multi-output transcripts with well-defined stoichiometric control. This module was further applied to signaling cascades for combined signal transduction and multi-input/multi-output synthetic devices. Further, the synTCEs can precisely manipulate the N-terminal ends of output proteins, facilitating effective protein localization and cellular population control. Therefore, the synTCEs could enhance computational capability and applicability of riboregulators for reprogramming biological systems, leading to future applications in synthetic biology, metabolic engineering and biotechnology.

Forget to Learn (F2L): Circumventing plasticity–stability trade-off in continuous unsupervised domain adaptation

In continuous unsupervised domain adaptation (CUDA), deep learning models struggle with the stability-plasticity trade-off—where the model must forget old knowledge to acquire new one. This paper introduces the “Forget to Learn” (F2L), a novel framework that circumvents such a trade-off. In contrast to state-of-the-art methods that aim to balance the two conflicting objectives, stability and plasticity, F2L utilizes active forgetting and knowledge distillation to circumvent the conflict’s root causes. In F2L, dual-encoders are trained, where the first encoder – the ‘Specialist’ – is designed to actively forget, thereby boosting adaptability (i.e., plasticity) and generating high-accuracy pseudo labels on the new domains. Such pseudo labels are then used to transfer/accumulate the specialist knowledge to the second encoder—the ‘Generalist’ through conflict-free knowledge distillation. Empirical and ablation studies confirmed F2L’s superiority on different datasets and against different SOTAs. Furthermore, F2L minimizes the need for hyperparameter tuning, enhances computational and sample efficiency, and excels in problems with long domain sequences—key advantages for practical systems constrained by hardware limitations.

Genome-wide identification of shaker K+ channel gene family in sugar beet (Beta vulgaris L.) and function of BvSKOR in response to salt and drought stresses

Potassium (K+) is the most abundant cation in plants, which is absorbed by roots and distributed throughout the plants and within plant cells, and is involved in various cellular processes. Shaker K+ channel plays crucial roles in the absorption and distribution of K+ and in the response to abiotic stress in plants. Herein, a total of six shaker K+ channel genes, BvKAT1, BvKAT3, BvAKT1, BvAKT2, BvAKT5, and BvSKOR, were identified in the genome of sugar beet (Beta vulgaris L.). The coding domain sequences (CDS) of these genes ranged from 2232 to 2739 bp, and protein lengths were varied from 743 to 912 aa. The shaker K+ channel genes contained hormone-related and light responsiveness cis-acting regulatory elements. The phylogenetic analysis showed that BvSKOR was highly conserved and contained six transmembrane structures. The expression patterns of BvSKOR under salt and osmotic stress were analyzed by qRT-PCR, and found that the expression level of BvSKOR under low concentration salt and osmotic stress at short period of treatment were significantly higher than that of the control group. The function of BvSKOR was further verified in tobacco (Nicotiana tabacum), and the results showed that under salt and osmotic stress, the roots of transgenic plants were significantly stronger than those of wild type (WT) plants, and the relative water content (RWC), chlorophyll, proline, soluble sugar, soluble proteins contents and antioxidant enzyme activity were significantly higher than those of WT plants. These results indicated that overexpression of BvSKOR can significantly enhance the salt and drought tolerance in transgenic tobacco plants. This study could provide theoretical support and genetic resources for genetic improvement of crops stress resistance.

Construction of multilayered gene circuits using de-novo-designed synthetic transcriptional regulators in cell-free systems

BackgroundDe-novo-designed synthetic transcriptional regulators have great potential as the genetic parts for constructing complex multilayered gene circuits. The design flexibility afforded by advanced nucleic acid sequence design tools vastly expands the repertoire of regulatory elements for circuit design. In principle, the design space of synthetic regulators should allow for the construction of regulatory circuits of arbitrary complexity; still, the orthogonality and robustness of such components have not been fully elucidated, thereby limiting the depth and width of synthetic circuits.ResultsIn this work, we systematically explored the design strategy of synthetic transcriptional regulators, termed switchable transcription terminators. Specifically, by redesigning key sequence domains, we created a high-performance switchable transcription terminator with a maximum fold change of 283.11 upon activation by its cognate input RNA. Further, an automated design algorithm was developed for these elements to improve orthogonality for a complex multi-layered circuit construction. The resulting orthogonal switchable transcription terminators could be used to construct a three-layer cascade circuit and a two-input three-layer OR gate.ConclusionsWe demonstrated a practical strategy for designing standardized regulatory elements and assembling modular gene circuits, ultimately laying the foundation for the streamlined construction of complex synthetic gene circuits.

A trivalent mucosal vaccine encoding phylogenetically inferred ancestral RBD sequences confers pan-Sarbecovirus protection in mice.

The continued emergence of SARS-CoV-2 variants and the threat of future Sarbecovirus zoonoses have spurred the design of vaccines that can induce broad immunity against multiple coronaviruses. Here, we use computational methods to infer ancestral phylogenetic reconstructions of receptor binding domain (RBD) sequences across multiple Sarbecovirus clades and incorporate them into a multivalent adenoviral-vectored vaccine. Mice immunized with this pan-Sarbecovirus vaccine are protected in the upper and lower respiratory tracts against infection by historical and contemporary SARS-CoV-2 variants, SARS-CoV, and pre-emergent SHC014 and Pangolin/GD coronavirus strains. Using genetic and immunological approaches, we demonstrate that vaccine-induced protection unexpectedly is conferred principally by CD4+ and CD8+ Tcell-mediated anamnestic responses. Importantly, prior mRNA vaccination or SARS-CoV-2 respiratory infection does not alter the efficacy of the mucosally delivered pan-Sarbecovirus vaccine. These data highlight the promise of a phylogenetic approach for antigen and vaccine design against existing and pre-emergent Sarbecoviruses with pandemic potential.

Establishment of the auxin inducible degron system for Babesia duncani: a conditional knockdown tool to study precise protein regulation in Babesia spp.

BackgroundBabesia duncani is a pathogen within the phylum Apicomplexa that causes human babesiosis. It poses a significant threat to public health, as it can be transmitted not only through tick bites but also via blood transfusion. Consequently, an understanding of the gene functions of this pathogen is necessary for the development of drugs and vaccines. However, the absence of conditional gene knockdown tools has hindered the research on this pathogen. The auxin-inducible degron (AID) system is a rapid, reversible conditional knockdown system widely used in gene function studies. Thus, there is an urgent need to establish the AID system in B. duncani to study essential gene functions.MethodsThe endogenous genes of the Skp1-Cullin-F-box (SCF) complex in B. duncani were identified and confirmed through multiple sequence alignment and conserved domain analysis. The expression of the F-box protein TIR1 from Oryza sativa (OsTIR1) was achieved by constructing a transgenic parasite strain using a homologous recombination strategy. Polymerase chain reaction (PCR), western blot, and indirect immunofluorescence assay (IFA) were used to confirm the correct monoclonal parasite strain. The degradation of enhanced green fluorescent protein (eGFP) tagged with an AID degron was detected through western blot and live-cell fluorescence microscopy after treatment of indole-3-acetic acid (IAA).ResultsIn this study, Skp1, Cul1, and Rbx1 of the SCF complex in B. duncani were identified through sequence alignment and domain analysis. A pure BdTIR1 strain with expression of the OsTIR1 gene was constructed through homologous recombination and confirmed. This strain showed no significant differences from the wild type (WT) in terms of growth rate and proportions of different parasite forms. The eGFP tagged with an AID degron was successfully induced for degradation using 500 μM IAA. Grayscale analysis of western blot indicated a 61.3% reduction in eGFP expression levels, while fluorescence intensity analysis showed a 77.5% decrease in fluorescence intensity. Increasing the IAA concentration to 2 mM accelerated eGFP degradation and enhanced the extent of degradation.ConclusionsThis study demonstrated the functionality of the AID system in regulating protein levels by inducing rapid degradation of eGFP using IAA, providing an important research tool for studying essential gene functions related to invasion, egress, and virulence of B. duncani. Moreover, it also offers a construction strategy for apicomplexan parasites that have not developed an AID system.Graphical

Addressing the antibody germline bias and its effect on language models for improved antibody design.

The versatile binding properties of antibodies have made them an extremely important class of biotherapeutics. However, therapeutic antibody development is a complex, expensive, and time-consuming task, with the final antibody needing to not only have strong and specific binding but also be minimally impacted by developability issues. The success of transformer-based language models in protein sequence space and the availability of vast amounts of antibody sequences, has led to the development of many antibody-specific language models to help guide antibody design. Antibody diversity primarily arises from V(D)J recombination, mutations within the CDRs, and/or from a few nongermline mutations outside the CDRs. Consequently, a significant portion of the variable domain of all natural antibody sequences remains germline. This affects the pre-training of antibody-specific language models, where this facet of the sequence data introduces a prevailing bias toward germline residues. This poses a challenge, as mutations away from the germline are often vital for generating specific and potent binding to a target, meaning that language models need be able to suggest key mutations away from germline. In this study, we explore the implications of the germline bias, examining its impact on both general-protein and antibody-specific language models. We develop and train a series of new antibody-specific language models optimized for predicting nongermline residues. We then compare our final model, AbLang-2, with current models and show how it suggests a diverse set of valid mutations with high cumulative probability. AbLang-2 is trained on both unpaired and paired data, and is freely available at https://github.com/oxpig/AbLang2.git.

Characterization of ATP-dependent phosphofructokinase genes during ripening and their modulation by phytohormones during postharvest storage of citrus fruits (Citrus reticulata Blanco.)

The level of sweetness in citrus fruit is crucial for consumer appeal and market competitiveness, determined mainly by soluble sugars and organic acids. ATP-dependent 6-phosphofructokinase is central to regulating sugar metabolism, yet its role in citrus fruit ripening and postharvest storage remains underexplored. We characterized phosphofructokinase genes in citrus, identifying eight genes classified into pyrophosphate-dependent phosphofructokinase (PFP) and ATP-dependent 6-phosphofructokinase (PFK) subgroups using phylogenetic analysis, genomic architectures, and protein motifs. Comparative genomic analysis with other plants highlighted significant protein homology among CitPFKs. The motif analysis indicated conserved phosphofructokinase domains in CitPFK sequences, with upstream promoter regions containing diverse cis-regulatory elements, most notably light-responsive (LREs). The gene expression profiling throughout fruit development and ripening revealed differential patterns, with responses to gibberellic acid and salicylic acid phytohormones during postharvest indicating their roles in regulating CitPFK genes. The analysis of the transcriptome showed high expression of ATP-dependent 6-phosphofructokinase 3 (CitPFK3) during fruit development, indicating a positive role in fruit maturation. Consequently, silencing CitPFK3 through virus-induced gene silencing (VIGS) increased hexose sugar content, suggesting its function in sugar accumulation. These findings improve our understanding of PFKs in citrus, particularly CitPFK3's pivotal role in regulating hexose sugar dynamics and their modulation by exogenous phytohormones after harvest. This study provides a foundation for optimizing soluble sugar regulation to enhance fruit quality and postharvest handling in citrus production.

De-noising magnetotelluric data based on machine learning

The magnetotelluric (MT) sounding is a common geophysical exploration technique, but it is highly polluted by various types of cultural noise. In the realm of MT data processing, traditional techniques often rely on the quality of the measured MT data. Conventional MT time domain denoising methods tend to eliminate valuable signals, potentially leading to unreliable resistivity estimates. To address this concern, we propose employing machine learning to effectively suppress strong noise interference in MT data, thereby preventing the loss of valuable signals. We augment this approach with mathematical morphological filtering (MMF) to capture low-frequency signals, preserving their integrity. We constructed a signal sample library based on a substantial volume of signal samples. Through consistent training, we establish a support vector machine (SVM) classification model that distinguishes high-quality signal fragments from noisy signals. Subsequently, we use adaptive K-singular value decomposition (K-SVD) dictionary learning to extract noise profiles and suppress noisy signals. To validate the feasibility of our method, we apply machine learning to measured data from two distinct observation areas. The measured data were analyzed and processed, and the results were compared with the robust results. This method can effectively eliminate large-scale strong interference in time domain sequences and preserve more low-frequency slow change information and high-quality signals in the reconstructed signals. The apparent resistivity phase curve of synthetic data is smoother and more continuous, and the data quality in the low-frequency range is significantly improved. The results can more accurately and reliably reflect underground electrical structure information.

A TDLAS gas detection method based on digital signal modulation

This research presents a novel TDLAS gas concentration detection method based on digital modulation. The method inherits the advantage of a simple system structure from Direct Absorption Spectroscopy, as well as the excellent sensitivity of Wavelength Modulation Spectroscopy. A low-frequency sawtooth wave is employed to drive the laser, resulting in a digital direct absorption spectrum signal. By constructing a cosine modulation sequence in the time domain and performing linear interpolation on the direct absorption spectrum, it successfully converts to a wavelength-modulated absorption spectrum and simultaneously generates a digital reference signal at double the frequency. Ultimately, phase-locked amplification technology can be used to calculate the amplitude of the second harmonic. Since both the modulation and reference signals are generated digitally, they ensure a strict frequency-doubling relationship and phase correlation, which not only reduces the complexity of the hardware system but also effectively minimizes system errors. Because digital technology generates both the modulation and reference signals, it ensures that they have the same phase and a strict frequency-doubling relationship. Experimental results demonstrate that, when fitted by a cubic polynomial, the second harmonic amplitude and the gas concentration have a correlation coefficient (R2) as high as 0.99999 and a root mean square error as low as 0.0011. This proves the method's great accuracy and reliability in practical applications.

Comparison of the Neutralization Power of Sotrovimab Against SARS-CoV-2 Variants: Development of a Rapid Computational Method.

The rapid evolution of SARS-CoV-2 imposed a huge challenge on disease control. Immune evasion caused by genetic variations of the SARS-CoV-2 spike protein's immunogenic epitopes affects the efficiency of monoclonal antibody-based therapy of COVID-19. Therefore, a rapid method is needed to evaluate the efficacy of the available monoclonal antibodies against the new emerging variants or potential novel variants. The aim of this study is to develop a rapid computational method to evaluate the neutralization power of anti-SARS-CoV-2 monoclonal antibodies against new SARS-CoV-2 variants and other potential new mutations. The amino acid sequence of the extracellular domain of the spike proteins of the severe acute respiratory syndrome coronavirus (GenBank accession number YP_009825051.1) and SARS-CoV-2 (GenBank accession number YP_009724390.1) were used to create computational 3D models for the native spike proteins. Specific mutations were introduced to the curated sequence to generate the different variant spike models. The neutralization potential of sotrovimab (S309) against these variants was evaluated based on its molecular interactions and Gibbs free energy in comparison to a reference model after molecular replacement of the reference receptor-binding domain with the variant's receptor-binding domain. Our results show a loss in the binding affinity of the neutralizing antibody S309 with both SARS-CoV and SARS-CoV-2. The binding affinity of S309 was greater to the Alpha, Beta, Gamma, and Kappa variants than to the original Wuhan strain of SARS-CoV-2. However, S309 showed a substantially decreased binding affinity to the Delta and Omicron variants. Based on the mutational profile of Omicron subvariants, our data describe the effect of the G339H and G339D mutations and their role in escaping antibody neutralization, which is in line with published clinical reports. This method is rapid, applicable, and of interest to adapt the use of therapeutic antibodies to the treatment of emerging variants. It could be applied to antibody-based treatment of other viral infections.

An Analysis of Combined Molecular Weight and Hydrophobicity Similarity between the Amino Acid Sequences of Spike Protein Receptor Binding Domains of Betacoronaviruses and Functionally Similar Sequences from Other Virus Families

Recently, we proposed a new method, based on protein profiles derived from physicochemical dynamic time warping (PCDTW), to functionally/structurally classify coronavirus spike protein receptor binding domains (RBD). Our method, as used herein, uses waveforms derived from two physicochemical properties of amino acids (molecular weight and hydrophobicity (MWHP)) and is designed to reach into the twilight zone of homology, and therefore, has the potential to reveal structural/functional relationships and potentially homologous relationships over greater evolutionary time spans than standard primary sequence alignment-based techniques. One potential application of our method is inferring deep evolutionary relationships such as those between the RBD of the spike protein of betacoronaviruses and functionally similar proteins found in other families of viruses, a task that is extremely difficult, if not impossible, using standard multiple alignment-based techniques. Here, we applied PCDTW to compare members of four divergent families of viruses to betacoronaviruses in terms of MWHP physicochemical similarity of their RBDs. We hypothesized that some members of the families Arteriviridae, Astroviridae, Reoviridae (both from the genera rotavirus and orthoreovirus considered separately), and Toroviridae would show greater physicochemical similarity to betacoronaviruses in protein regions similar to the RBD of the betacoronavirus spike protein than they do to other members of their respective taxonomic groups. This was confirmed to varying degrees in each of our analyses. Three arteriviruses (the glycoprotein-2 sequences) clustered more closely with ACE2-binding betacoronaviruses than to other arteriviruses, and a clade of 33 toroviruses was found embedded within a clade of non-ACE2-binding betacoronaviruses, indicating potentially shared structure/function of RBDs between betacoronaviruses and members of other virus clades.

Putative MutS2 Homologs in Algae: More Goods in Shopping Bag?

MutS2 proteins are presumably involved in either control of recombination or translation quality control in bacteria. MutS2 homologs have been found in plants and some algae; however, their actual diversity in eukaryotes remains unknown. We found putative MutS2 homologs in various species of photosynthetic eukaryotes and performed a detailed analysis of the revealed amino acid sequences. Three groups of homologs were distinguished depending on their domain composition: MutS2 homologs with full set of specific domains, MutS2-like sequences without endonuclease Smr domain, and MutS2-like homologs lacking Smr and clamp in domain IV, the extreme form of which are proteins with only a complete ATPase domain. We clarified the information about amino acid composition and set of specific motifs in the conserved domains in MutS2 and MutS2-like sequences. The models of the predicted tertiary structure were obtained for each group of homologs. The phylogenetic analysis demonstrated that all eukaryotic sequences split into two large groups. The first group included homologs belonging to species of Archaeplastida and a subset of haptophyte homologs, while the second-sequences of organisms from CASH groups (cryptophytes, alveolates, stramenopiles, haptophytes) and chlorarachniophytes. The cyanobacterial MutS2 clustered together with the first group, and proteins belonging to Deltaproteobacteria (orders Myxococcales and Bradymonadales) showed phylogenetic affinity to the CASH-including group with strong support. The observed tree pattern did not support a clear differentiation of eukaryotes into lineages with red and green algae-derived plastids. The results are discussed in the context of current conceptions of serial endosymbioses and genetic mosaicism in algae with complex plastids.

A-031 Development of novel ELISAs for total GDF-15 and H-specific GDF-15

Abstract Background To develop sensitive and specific ELISAs for the quantitative measurement of total human GDF-15 and H-specific (H202D mutant) GDF-15 in human serum, and other biological fluids. Growth/differentiation Factor 15 (GDF-15) is a divergent member of the TGF-β superfamily of growth factors. It is encoded in humans by a gene in chromosome 19. The human GDF-15 gene encodes for a protein of 308 amino acid residues which consists of a signal sequence (residues 1-29), pro-domain (30-194), and mature growth factor domain (195-308). The molecular weight of a mature GDF-15 dimer is 25 kDa. Approximately 25% of humans have a missense polymorphism in the GDF-15 gene resulting in mutation of histidine 202 to aspartate (histidine 6 in the mature domain), close to the N-terminus of the mature growth factor. This variant is associated with phenotypes in prostate cancer, hyperemesis gravidarum, (severe morning sickness in pregnancy), and rheumatoid arthritis. Methods Highly specific and reproducible total GDF-15 (AL-1014-r) and H-specific GDF-15 (AL-1018-r) ELISAs have been developed using specific monoclonal antibodies to help estimate the total and mutant (DD) concentration in serum in the respective assays. The ELISAs use 10 uL sample volume and are calibrated to recombinant human GDF-15 from R & D Systems (Biotechne, USA). These ELISAs were validated for their specificity using HH, DD, HD recombinant preparations and their circulating levels in male, female, 1st, and 2nd-trimester serum samples. Results The Total GDF-15 ELISA assay detects total GDF-15 including histidine 202 to aspartate mutation (HH, HD & DD variant) in the mature domain in equimolar proportions. The H-specific GDF-15 assay is specific to histidine at 202aa in the GDF-15 sequence and does not detect histidine 202 to aspartate mutation (DD variant). Median Levels of total GDF-15 in healthy males (n=18), females (n=17), 1st trimester (n=20), and 2nd trimester (n=20) were 847.9 pg/mL, 1182.4 pg/mL, 12759.7 pg/mL, and 12951.2 pg/mL. Median Levels of H-specific GDF-15 in healthy males (n=18), females (n=17), 1st trimester (n=20), and 2nd trimester (n=20) were 723.2 pg/mL, 641.3 pg/mL, 8381.4 pg/mL and 4652.1 pg/mL. Method comparison between total GDF-15 and commercial GDF-15 assay using serum samples (HH, wild type) in the range of 400-2500 pg/mL yielded a slope of 0.98 (r=0.97). The HD and DD mutant samples in the total assay recovered at twice the concentrations of the commercial assay. The total and intact assays are highly reproducible with the total coefficient of variation less than 7%. Conclusions Use of total GDF-15 assay in combination with the GDF-15 H-specific assay (DD nondetectable) ELISA can accurately estimate the mutant (DD) concentration in serum. This will enhance the knowledge of the GDF-15 measurements in the literature as the commercial assays were compromised for its immunoreactivity to the HD DD genotypes which is highly prevalent.

Non-coherent short-packet communications: Novel z-domain user multiplexing

In the evolution of fifth generation (5G) and beyond wireless communication systems, non-coherent (NC) short packet communication (SPC) is crucial for achieving ultra-reliable low-latency communication (URLLC). Frame design, latency, and reliability are some of the challenges associated with short-packet communication. Recently, to address these challenges, a novel modulation scheme known as modulation on conjugate-reciprocal zeros (MOCZ) has been proposed. MOCZ modulates information on conjugate reciprocal zeros in the z-domain, thereby eliminating the need for channel estimation and providing a robust solution for NC communication. However, in multi-user MOCZ (MU-MOCZ) scheme, adding guard intervals to each short packet to mitigate channel impact remains an issue, as it increases the transmission time and consequently reduces efficiency. To address the aforementioned problem, this paper introduces a novel frame design approach called z-domain user multiplexing MOCZ (ZDUM-MOCZ or ZDM-MOCZ). Unlike traditional time division multiplexing (TDM), which serves users consecutively in the time domain, this method multiplexes users in the z-domain. In this approach, each user is allocated a specific set of zeros in the z-domain, which collectively form a unique sequence in the time domain. The findings illustrate the potential for reduced latency in downlink transmission, highlighting the benefits of this novel methodology over conventional MU-MOCZ method. The proposed ZDUM-MOCZ scheme not only addresses the existing issues in the frame design of the MU-MOCZ scheme but also facilitates more efficient and reliable short packet communication in 5G and beyond wireless systems.