Low Sequence Research Articles

Functional and structural characterisation of RimL from Bacillus cereus, a new Nα-acetyltransferase of ribosomal proteins that was wrongly assigned as an aminoglycosyltransferase

Enzymes of the GNAT (GCN5-relate N-acetyltransferases) superfamily are important regulators of cell growth and development. They are functionally diverse and share low amino acid sequence identity, making functional annotation difficult. In this study, we report the function and structure of a new ribosomal enzyme, Nα-acetyl transferase from Bacillus cereus (RimLBC), a protein that was previously wrongly annotated as an aminoglycosyltransferase. Firstly, extensive comparative amino acid sequence analyses suggested RimLBC belongs to a cluster of proteins mediating acetylation of the ribosomal protein L7/L12. To assess if this was the case, several well established substrates of aminoglycosyltransferases were screened. The results of these studies did not support an aminoglycoside acetylating function for RimLBC. To gain further insight into RimLBC biological role, a series of studies that included MALDI-TOF, isothermal titration calorimetry, NMR, X-ray protein crystallography, and site-directed mutagenesis confirmed RimLBC affinity for Acetyl-CoA and that the ribosomal protein L7/L12 is a substrate of RimLBC. Last, we advance a mechanistic model of RimLBC mode of recognition of its protein substrates. Taken together, our studies confirmed RimLBC as a new ribosomal Nα-acetyltransferase and provide structural and functional insights into substrate recognition by Nα-acetyltransferases and protein acetylation in bacteria.

Biochemical characterization of L-asparaginase isoforms from Rhizobium etli-the boosting effect of zinc.

L-Asparaginases, divided into three structural Classes, catalyze the hydrolysis of L-asparagine to L-aspartic acid and ammonia. The members of Class 3, ReAIV and ReAV, encoded in the genome of the nitrogen fixing Rhizobium etli, have the same fold, active site, and quaternary structure, despite low sequence identity. In the present work we examined the biochemical consequences of this difference. ReAIV is almost twice as efficient as ReAV in asparagine hydrolysis at 37°C, with the kinetic KM, kcat parameters (measured in optimal buffering agent) of 1.5mM, 770s-1 and 2.1mM, 603s-1, respectively. The activity of ReAIV has a temperature optimum at 45°C-55°C, whereas the activity of ReAV, after reaching its optimum at 37°C, decreases dramatically at 45°C. The activity of both isoforms is boosted by 32 or 56%, by low and optimal concentration of zinc, which is bound three times more strongly by ReAIV then by ReAV, as reflected by the KD values of 1.2 and 3.3μM, respectively. We also demonstrate that perturbation of zinc binding by Lys→Ala point mutagenesis drastically decreases the enzyme activity but also changes the mode of response to zinc. We also examined the impact of different divalent cations on the activity, kinetics, and stability of both isoforms. It appeared that Ni2+, Cu2+, Hg2+, and Cd2+ have the potential to inhibit both isoforms in the following order (from the strongest to weakest inhibitors) Hg2+ > Cu2+ > Cd2+ > Ni2+. ReAIV is more sensitive to Cu2+ and Cd2+, while ReAV is more sensitive to Hg2+ and Ni2+, as revealed by IC50 values, melting scans, and influence on substrate specificity. Low concentration of Cd2+ improves substrate specificity of both isoforms, suggesting its role in substrate recognition. The same observation was made for Hg2+ in the case of ReAIV. The activity of the ReAV isoform is less sensitive to Cl- anions, as reflected by the IC50 value for NaCl, which is eightfold higher for ReAV relative to ReAIV. The uncovered complementary properties of the two isoforms help us better understand the inducibility of the ReAV enzyme.

Storing Images in DNA via base128 Encoding.

Current DNA storage schemes lack flexibility and consistency in processing highly redundant and correlated image data, resulting in low sequence stability and image reconstruction rates. Therefore, according to the characteristics of image storage, this paper proposes storing images in DNA via base128 encoding (DNA-base128). In the data writing stage, data segmentation and probability statistics are carried out, and then, the data block frequency and constraint encoding set are associated with achieving encoding. When the image needs to be recovered, DNA-base128 completes internal error correction by threshold setting and drift comparison. Compared with representative work, the DNA-base128 encoding results show that the undesired motifs were reduced by 71.2-90.7% and that the local guanine-cytosine content variance was reduced by 3 times, indicating that DNA-base128 can store images more stably. In addition, the structural similarity index (SSIM) and multiscale structural similarity (MS-SSIM) of image reconstruction using DNA-base128 were improved by 19-102 and 6.6-20.3%, respectively. In summary, DNA-base128 provides image encoding with internal error correction and provides a potential solution for DNA image storage. The data and code are available at the GitHub repository: https://github.com/123456wk/DNA_base128.

Real-time visual SLAM based YOLO-Fastest for dynamic scenes

Within the realm of autonomous robotic navigation, simultaneous localization and mapping (SLAM) serves as a critical perception technology, drawing heightened attention in contemporary research. The traditional SLAM systems perform well in static environments, but in the real physical world, dynamic objects can destroy the static geometric constraints of the SLAM system, further limiting its practical application in the real world. In this paper, a robust dynamic RGB-D SLAM system is proposed to expand the number of static points in the scene by combining with YOLO-Fastest to ensure the effectiveness of the geometric constraints model construction, and then based on that, a new thresholding model is designed to differentiate the dynamic features in the objection bounding box, which takes advantage of the double polyline constraints and the residuals after reprojection to filter the dynamic feature points. In addition, two Gaussian models are constructed to segment the moving objects in the bounding box in the depth image to achieve the effect similar to the instance segmentation under the premise of ensuring the computational speed. In this paper, experiments are conducted on dynamic sequences provided by the TUM dataset to evaluate the performance of the proposed method, and the results show that the root mean squared error metric of the absolute trajectory error of the algorithm of this paper has at least 80% improvement compared to ORB-SLAM2. Higher robustness in dynamic environments with both high and low dynamic sequences compared to DS-SLAM and Dynaslam, and can effectively provide intelligent localization and navigation for mobile robots.

Synthetic self-adjuvanted multivalent Mucin 1 (MUC1) glycopeptide vaccines with improved in vivo antitumor efficacy.

The tumor-associated glycoprotein Mucin 1 (MUC1) is aberrantly glycosylated on cancer cells and is considered a promising target for antitumor vaccines. The weak immunogenicity and low sequence homology of mouse mucins and human MUC1 are the main obstacles for the development of vaccines. Herein, a self-adjuvanted strategy combining toll-like receptor 2 lipopeptide ligands and T-cell epitopes and the multivalent effect were used to amplify the immune response and evade the unpredictable immunogenicity, generating two self-adjuvanted three-component MUC1 vaccines (mono- and trivalent MUC1 vaccines). To simulate the aberrantly glycosylated MUC1 glycoprotein, the MUC1 tandem repeat peptide was bounded with Tn antigens at T9, S15, and T16, and served as B-cell epitopes. Results showed that both vaccines elicited a robust antibody response in wild-type mice compared with a weaker response in MUC1 transgenic mice. The trivalent vaccine did not elevate the antibody response level compared with the monovalent vaccine; however, a more delayed tumor growth and prolonged survival time was realized in wild-type and transgenic mouse models treated with the trivalent vaccine. These results indicate that the self-adjuvanted three-component MUC1 vaccines, especially the trivalent vaccine, can trigger robust antitumor effects regardless of sequence homology, and, therefore, show promise for clinical translation.

Making Use of Averaging Methods in MODELLER for Protein Structure Prediction.

Recent advances in protein structure prediction, driven by AlphaFold 2 and machine learning, demonstrate proficiency in static structures but encounter challenges in capturing essential dynamic features crucial for understanding biological function. In this context, homology-based modeling emerges as a cost-effective and computationally efficient alternative. The MODELLER (version 10.5, accessed on 30 November 2023) algorithm can be harnessed for this purpose since it computes intermediate models during simulated annealing, enabling the exploration of attainable configurational states and energies while minimizing its objective function. There have been a few attempts to date to improve the models generated by its algorithm, and in particular, there is no literature regarding the implementation of an averaging procedure involving the intermediate models in the MODELLER algorithm. In this study, we examined MODELLER's output using 225 target-template pairs, extracting the best representatives of intermediate models. Applying an averaging procedure to the selected intermediate structures based on statistical potentials, we aimed to determine: (1) whether averaging improves the quality of structural models during the building phase; (2) if ranking by statistical potentials reliably selects the best models, leading to improved final model quality; (3) whether using a single template versus multiple templates affects the averaging approach; (4) whether the "ensemble" nature of the MODELLER building phase can be harnessed to capture low-energy conformations in holo structures modeling. Our findings indicate that while improvements typically fall short of a few decimal points in the model evaluation metric, a notable fraction of configurations exhibit slightly higher similarity to the native structure than MODELLER's proposed final model. The averaging-building procedure proves particularly beneficial in (1) regions of low sequence identity between the target and template(s), the most challenging aspect of homology modeling; (2) holo protein conformations generation, an area in which MODELLER and related tools usually fall short of the expected performance.

Massilia litorea sp. nov., Marinobacter salinisoli sp. nov. and Rhodobacter xanthinilyticus sp. nov., isolated from coastal environments.

Three bacterial strains, namely LPB0304T, LPB0319T and LPB0142T, were isolated from coastal environments. The 16S rRNA gene sequences of the three isolates were found to show the highest sequence similarities to Massilia litorea (98.44 %), Marinobacter salinisoli (97.55 %) and Rhodobacter lacus (97.60 %), respectively. The low (<98.7 %) sequence similarities and tree topologies implied the novelty of the three isolates, representing novel genomic species of the genus Massilia, Marinobacter and Rhodobacter. Numerous biochemical and physiological features also supported the distinctiveness of the isolates from previously known species. Based on the phenotypic and phylogenetic data presented in this study, three novel species are suggested with the following names: Massilia litorea sp. nov. (LPB0304T=KACC 21523T=ATCC TSD-216T), Marinobacter salinisoli sp. nov. (LPB0319T=KACC 21522T=ATCC TSD-218T) and Rhodobacter xanthinilyticus sp. nov. (LPB0142T=KACC 18892T=JCM 31567T).

Intrinsic protein disorder is insufficient to drive subnuclear clustering in embryonic transcription factors.

Modern microscopy has revealed that core nuclear functions, including transcription, replication, and heterochromatin formation, occur in spatially restricted clusters. Previous work from our lab has shown that subnuclear high-concentration clusters of transcription factors may play a role in regulating RNA synthesis in the early Drosophila embryo. A nearly ubiquitous feature of eukaryotic transcription factors is that they contain intrinsically disordered regions (IDRs) that often arise from low complexity amino acid sequences within the protein. It has been proposed that IDRs within transcription factors drive co-localization of transcriptional machinery and target genes into high-concentration clusters within nuclei. Here, we test that hypothesis directly, by conducting a broad survey of the subnuclear localization of IDRs derived from transcription factors. Using a novel algorithm to identify IDRs in the Drosophila proteome, we generated a library of IDRs from transcription factors expressed in the early Drosophila embryo. We used this library to perform a high-throughput imaging screen in Drosophila Schneider-2 (S2) cells. We found that while subnuclear clustering does not occur when the majority of IDRs are expressed alone, it is frequently seen in full-length transcription factors. These results are consistent in live Drosophila embryos, suggesting that IDRs are insufficient to drive the subnuclear clustering behavior of transcription factors. Furthermore, the clustering of transcription factors in living embryos was unaffected by the deletion of IDR sequences. Our results demonstrate that IDRs are unlikely to be the primary molecular drivers of the clustering observed during transcription, suggesting a more complex and nuanced role for these disordered protein sequences.

Intrinsic protein disorder is insufficient to drive subnuclear clustering in embryonic transcription factors

Modern microscopy has revealed that core nuclear functions, including transcription, replication, and heterochromatin formation, occur in spatially restricted clusters. Previous work from our lab has shown that subnuclear high-concentration clusters of transcription factors may play a role in regulating RNA synthesis in the early Drosophila embryo. A nearly ubiquitous feature of eukaryotic transcription factors is that they contain intrinsically disordered regions (IDRs) that often arise from low complexity amino acid sequences within the protein. It has been proposed that IDRs within transcription factors drive co-localization of transcriptional machinery and target genes into high-concentration clusters within nuclei. Here, we test that hypothesis directly, by conducting a broad survey of the subnuclear localization of IDRs derived from transcription factors. Using a novel algorithm to identify IDRs in the Drosophila proteome, we generated a library of IDRs from transcription factors expressed in the early Drosophila embryo. We used this library to perform a high-throughput imaging screen in Drosophila Schneider-2 (S2) cells. We found that while subnuclear clustering does not occur when the majority of IDRs are expressed alone, it is frequently seen in full-length transcription factors. These results are consistent in live Drosophila embryos, suggesting that IDRs are insufficient to drive the subnuclear clustering behavior of transcription factors. Furthermore, the clustering of transcription factors in living embryos was unaffected by the deletion of IDR sequences. Our results demonstrate that IDRs are unlikely to be the primary molecular drivers of the clustering observed during transcription, suggesting a more complex and nuanced role for these disordered protein sequences.

Detection of Felis catus Gammaherpesvirus 1 in Domestic Cat Saliva: Prevalence, Risk Factors, and Attempted Virus Isolation.

Felis catus gammaherpesvirus 1 (FcaGHV1) infects domestic cats worldwide, yet it has not been successfully propagated in cell culture, and little is known about how it is shed and transmitted. To investigate the salivary shedding of FcaGHV1, we quantified FcaGHV1 DNA in feline saliva by qPCR. For FcaGHV1-positive saliva, we sequenced a portion of the viral glycoprotein B (gB) gene and attempted to isolate the infectious virus by passage in several felid and non-felid cell lines. We detected FcaGHV1 DNA in 45/227 (19.8%) saliva samples with variable viral DNA loads from less than 100 to greater than 3 million copies/mL (median 4884 copies/mL). Multiple saliva samples collected from an infected cat over a two-month period were consistently positive, indicating that chronic shedding can occur for at least two months. Cat age, sex, and health status were not associated with shedding prevalence or viral DNA load in saliva. Feral status was also not associated with shedding prevalence. However, feral cats had significantly higher FcaGHV1 DNA load than non-feral cats. Sequencing of FcaGHV1 gB showed low sequence diversity and >99.5% nucleotide identity to the worldwide consensus FcaGHV1 gB sequence. We did not detect virus replication during the passage of FcaGHV1-positive saliva in cell culture, as indicated by consistently negative qPCR on cell lysate and supernatant. To our knowledge, these data show for the first time that cats in Canada are infected with FcaGHV1. The data further suggest that shedding of FcaGHV1 in saliva is common, can occur chronically over an extended period of time, and may occur at higher levels in feral compared to non-feral cats.

Analyzing genetic diversity of chloroplast genomes in Liliales

AbstractLiliales is a monocotyledonous order and contains both photosynthetic and mycoheterotrophic species that distribute locally or worldwide. In this study, thegenetic diversity of chloroplast genomes in Liliales was explored regarding theirnucleotide diversity and repeated composition. The analysis of nucleotide diversity revealed various hotspots in large and small single-copy regions whereas the IR regions had low sequence divergence. Although each family has specific hotspots, the rps15-ycf1 region was commonly found as a highly variable area in the cpDNA of observed taxa. In the cpDNA of Liliales, mononucleotide simple sequence repeat (SSR) is the most common type. The majority of SSRs are located in non-coding regions. Similarly, more long repeats were found in non-coding areas than in coding sequences. Additionally, the complement repeat exceeds forward type in the cpDNA of Liliales. The highest number of long repeats was found in Corsia dispar whereas that of SSRswas detected in Smilax china. The results of nucleotide diversity and repeat analyses provided fundamental information for further studies on population genetics, molecular marker development and evolutionary history of Liliales.® 2022 Journal of Science and Technology - NTTU

Biological ammonium transporters: evolution and diversification.

Although ammonium is the preferred nitrogen source for microbes and plants, in animal cells it is a toxic product of nitrogen metabolism that needs to be excreted. Thus, ammonium movement across biological membranes, whether for uptake or excretion, is a fundamental and ubiquitous biological process catalysed by the superfamily of the Amt/Mep/Rh transporters. A remarkable feature of the Amt/Mep/Rh family is that they are ubiquitous and, despite sharing low amino acid sequence identity, are highly structurally conserved. Despite sharing a common structure, these proteins have become involved in a diverse range of physiological process spanning all domains of life, with reports describing their involvement in diverse biological processes being published regularly. In this context, we exhaustively present their range of biological roles across the domains of life and after explore current hypotheses concerning their evolution to help to understand how and why the conserved structure fulfils diverse physiological functions.

In-Cell Association of a Bioorthogonal Tubulin.

Studies of proteins from one organism in another organism's cells have shown that such exogenous proteins stick more, pointing toward coevolution of the cytoplasm and protein surface to minimize stickiness. Here we flip this question around by asking whether exogenous proteins can assemble efficiently into their target complexes in a non-native cytoplasm. We use as our model system the assembly of BtubA and BtubB from Prosthecobacter hosted in human U-2 OS cells. BtubA and B evolved from eukaryotic tubulins after horizontal gene transfer, but they have low surface sequence identity with the homologous human tubulins and do not respond to tubulin drugs such as nocodazole. In U-2 OS cells, BtubA and B assemble efficiently into dimers compared to in vitro, and the wild-type BtubA and B proteins subsequently are able to form microtubules as well. We find that generic crowding effects (Ficoll 70 in vitro) contribute significantly to efficient dimer assembly when compared to sticking interactions (U-2 OS cell lysate in vitro), consistent with the notion that a generic mechanism such as crowding can be effective at driving assembly of exogenous proteins, even when protein-cytoplasm quinary structure and sticking have been modified in a non-native cytoplasm. A simple Monte Carlo model of in vitro and in-cell interactions, treating BtubA and B as sticky dipoles in a matrix of sticky or nonsticky crowders, rationalizes all the experimental trends with two adjustable parameters and reveals nucleation as the likely mechanism for the time-scale separation between dimer- and tubule formation in-cell and in vitro.

Comparative Structure-Based Virtual Screening Utilizing Optimized AlphaFold Model Identifies Selective HDAC11 Inhibitor.

HDAC11 is a class IV histone deacylase with no crystal structure reported so far. The catalytic domain of HDAC11 shares low sequence identity with other HDAC isoforms, which makes conventional homology modeling less reliable. AlphaFold is a machine learning approach that can predict the 3D structure of proteins with high accuracy even in absence of similar structures. However, the fact that AlphaFold models are predicted in the absence of small molecules and ions/cofactors complicates their utilization for drug design. Previously, we optimized an HDAC11 AlphaFold model by adding the catalytic zinc ion and minimization in the presence of reported HDAC11 inhibitors. In the current study, we implement a comparative structure-based virtual screening approach utilizing the previously optimized HDAC11 AlphaFold model to identify novel and selective HDAC11 inhibitors. The stepwise virtual screening approach was successful in identifying a hit that was subsequently tested using an in vitro enzymatic assay. The hit compound showed an IC50 value of 3.5 µM for HDAC11 and could selectively inhibit HDAC11 over other HDAC subtypes at 10 µM concentration. In addition, we carried out molecular dynamics simulations to further confirm the binding hypothesis obtained by the docking study. These results reinforce the previously presented AlphaFold optimization approach and confirm the applicability of AlphaFold models in the search for novel inhibitors for drug discovery.

Long- and short-read sequencing methods discover distinct circular RNA pools in Lotus japonicus.

Circular RNAs (circRNAs) are covalently closed single-stranded RNAs, generated through a back-splicing process that links a downstream 5' site to an upstream 3' end. The only distinction in the sequence between circRNA and their linear cognate RNA is the back splice junction. Their low abundance and sequence similarity with their linear origin RNA have made the discovery and identification of circRNA challenging. We have identified almost 6000 novel circRNAs from Lotus japonicus leaf tissue using different enrichment, amplification, and sequencing methods as well as alternative bioinformatics pipelines. The different methodologies identified different pools of circRNA with little overlap. We validated circRNA identified by the different methods using reverse transcription polymerase chain reaction and characterized sequence variations using nanopore sequencing. We compared validated circRNA identified in L. japonicus to other plant species and showed conservation of high-confidence circRNA-expressing genes. This is the first identification of L. japonicus circRNA and provides a resource for further characterization of their function in gene regulation. CircRNAs identified in this study originated from genes involved in all biological functions of eukaryotic cells. The comparison of methodologies and technologies to sequence, identify, analyze, and validate circRNA from plant tissues will enable further research to characterize the function and biogenesis of circRNA in L. japonicus.

Sponges and their prokaryotic communities sampled from a remote karst ecosystem

Marine karst ecosystems exist at the land-sea interface and are characterised by underwater formations sculpted over time by the action of seawater. Submerged caves and crevices of these ecosystems host a rich array of marine life of which sponges are among the most abundant and diverse components. In the present study, we describe elements of the sponge fauna sampled from a unique karst ecosystem at a remote island, Orchid Island, off the southeastern coast of Taiwan. The present study includes several understudied sponge taxa, including sclerosponges (Acanthochaetetes wellsi, and Astrosclera willeyana) and several lithistid species from dark, shallow-water caves. Prokaryotic communities were obtained from a total of 22 demosponge species, of which 11 are potentially new to science. The tetracladinid, lithistids harboured prokaryotic communities, which clustered separately from all other sponge species, contrasting with the non-tetracladinid, lithistid Vetulina incrustans. The tetracladinid, lithistids, furthermore, formed two distinct clusters with species of the Spirophorina suborder clustering apart from those of the Astrophorina suborder. The sclerosponge A. wellsi also harboured a distinct prokaryotic community in terms of composition including five unique, abundant OTUs with relatively low sequence similarities to organisms in GenBank. All cave sponges were enriched with SAR202 members, a group of bacteria known for their role in the degradation of recalcitrant compounds. The highest relative abundance of SAR202 was found in A. wellsi. We propose that the cave sponges of Orchid Island may play an as-yet uncharted role in nutrient dynamics at the land-sea interface.

Structure of a tripartite protein complex that targets toxins to the type VII secretion system.

Type VII secretion systems are membrane-embedded nanomachines used by Gram-positive bacteria to export effector proteins from the cytoplasm to the extracellular environment. Many of these effectors are polymorphic toxins comprised of an N-terminal Leu-x-Gly (LXG) domain of unknown function and a C-terminal toxin domain that inhibits the growth of bacterial competitors. In recent work, it was shown that LXG effectors require two cognate Lap proteins for T7SS-dependent export. Here, we present the 2.6 Å structure of the LXG domain of the TelA toxin from the opportunistic pathogen Streptococcus intermedius in complex with both of its cognate Lap targeting factors. The structure reveals an elongated α-helical bundle within which each Lap protein makes extensive hydrophobic contacts with either end of the LXG domain. Remarkably, despite low overall sequence identity, we identify striking structural similarity between our LXG complex and PE-PPE heterodimers exported by the distantly related ESX type VII secretion systems of Mycobacteria implying a conserved mechanism of effector export among diverse Gram-positive bacteria. Overall, our findings demonstrate that LXG domains, in conjunction with their cognate Lap targeting factors, represent a tripartite secretion signal for a widespread family of T7SS toxins.

Utilizing Precursor Ion Connectivity of Different Charge States to Improve Peptide and Protein Identification in MS/MS Analysis.

Tandem mass spectrometry (MS/MS) has become a key method for the structural analysis of biomolecules such as peptides and proteins. A pervasive problem in MS/MS analyses, especially for top-down proteomics, is the occurrence of chimeric spectra, when two or more precursor ions are co-isolated and fragmented, thus leading to complex MS/MS spectra that are populated with fragment ions originating from different precursor ions. This type of convoluted data typically results in low sequence database search scores due to the vast number of mixed-source fragment ions, of which only a fraction originates from a specific precursor ion. Herein, we present a novel workflow that deconvolutes the data of chimeric MS/MS spectra, improving the protein search scores and sequence coverages in database searching and thus providing a more confident peptide and protein identification. Previously misidentified proteins or proteins with insignificant search scores can be correctly and significantly identified following the presented data acquisition and analysis workflow with search scores increasing by a factor of 3-4 for smaller precursor ions (peptides) and >6 for larger precursor ions such as intact ubiquitin and cytochrome C.

Identification and characterization of a novel type of ketohexokinase from the haloarchaeon Haloferax volcanii.

Ketohexokinase (KHK) catalyzes the ATP-dependent phosphorylation of fructose, forming fructose-1-phosphate and ADP. The enzyme is well studied in Eukarya, in particular in humans and other vertebrates, but homologs have not been identified in Bacteria and Archaea. Here we report the identification of a novel type of KHK from the haloarchaeon Haloferax volcanii (HvKHK). The encoding gene khk was identified as HVO_1812. The gene was expressed as a 90-kDa homodimeric protein, catalyzing the phosphorylation of fructose with a Vmax value of 59 U/mg and apparent KM values for ATP and fructose of 0.47 and 1.29 mM, respectively. Homologs of HvKHK were only identified in a few haloarchaea and halophilic Bacteria. The protein showed low sequence identity to characterized KHKs from Eukarya and phylogenetic analyses indicate that haloarchaeal KHKs are largely separated from eukaryal KHKs. This is the first report of the identification of KHKs in prokaryotes that form a novel cluster of sugar kinases within the ribokinase/pfkB superfamily.

WAS IT A MATch I SAW? Approximate palindromes lead to overstated false match rates in benchmarks using reversed sequences.

Software for labeling biological sequences typically produces a theory-based statistic for each match (the E-value) that indicates the likelihood of seeing that match's score by chance. E-values accurately predict false match rate for comparisons of random (shuffled) sequences, and thus provide a reasoned mechanism for setting score thresholds that enable high sensitivity with low expected false match rate. This threshold-setting strategy is challenged by real biological sequences, which contain regions of local repetition and low sequence complexity that cause excess matches between non-homologous sequences. Knowing this, tool developers often develop benchmarks that use realistic-seeming decoy sequences to explore empirical tradeoffs between sensitivity and false match rate. A recent trend has been to employ reversed biological sequences as realistic decoys, because these preserve the distribution of letters and the existence of local repeats, while disrupting the original sequence's functional properties. However, we and others have observed that sequences appear to produce high scoring alignments to their reversals with surprising frequency, leading to overstatement of false match risk that may negatively affect downstream analysis. We demonstrate that an alignment between a sequence S and its (possibly mutated) reversal tends to produce higher scores than alignment between truly unrelated sequences, even when S is a shuffled string with no notable repetitive or low-complexity regions. This phenomenon is due to the unintuitive fact that (even randomly shuffled) sequences contain palindromes that are on average longer than the longest common substrings (LCS) shared between permuted variants of the same sequence. Though the expected palindrome length is only slightly larger than the expected LCS, the distribution of alignment scores involving reversed sequences is strongly right-shifted, leading to greatly increased frequency of high-scoring alignments to reversed sequences. Overestimates of false match risk can motivate unnecessarily high score thresholds, leading to potentially reduced true match sensitivity. Also, when tool sensitivity is only reported up to the score of the first matched decoy sequence, a large decoy set consisting of reversed sequences can obscure sensitivity differences between tools. As a result of these observations, we advise that reversed biological sequences be used as decoys only when care is taken to remove positive matches in the original (un-reversed) sequences, or when overstatement of false labeling is not a concern. Though the primary focus of the analysis is on sequence annotation, we also demonstrate that the prevalence of internal palindromes may lead to an overstatement of the rate of false labels in protein identification with mass spectrometry.