Benchmarks in antimicrobial peptide prediction are biased due to the selection of negative data.

Antimicrobial peptides (AMPs) are a heterogeneous group of short polypeptides that target not only microorganisms but also viruses and cancer cells. Due to their lower selection for resistance compared with traditional antibiotics, AMPs have been attracting the ever-growing attention from researchers, including bioinformaticians. Machine learning represents the most cost-effective method for novel AMP discovery and consequently many computational tools for AMP prediction have been recently developed. In this article, we investigate the impact of negative data sampling on model performance and benchmarking. We generated 660 predictive models using 12 machine learning architectures, a single positive data set and 11 negative data sampling methods; the architectures and methods were defined on the basis of published AMP prediction software. Our results clearly indicate that similar training and benchmark data set, i.e. produced by the same or a similar negative data sampling method, positively affect model performance. Consequently, all the benchmark analyses that have been performed for AMP prediction models are significantly biased and, moreover, we do not know which model is the most accurate. To provide researchers with reliable information about the performance of AMP predictors, we also created a web server AMPBenchmark for fair model benchmarking. AMPBenchmark is available at http://BioGenies.info/AMPBenchmark.

Testing Antimicrobial Properties of Human Lactoferrin-Derived Fragments.

Lactoferrin, an iron-binding glycoprotein, plays a significant role in the innate immune system, with antibacterial, antivirial, antifungal, anticancer, antioxidant and immunomodulatory functions reported. It is worth emphasizing that not only the whole protein but also its derived fragments possess antimicrobial peptide (AMP) activity. Using AmpGram, a top-performing AMP classifier, we generated three novel human lactoferrin (hLF) fragments: hLF 397-412, hLF 448-464 and hLF 668-683, predicted with high probability as AMPs. For comparative studies, we included hLF 1-11, previously confirmed to kill some bacteria. With the four peptides, we treated three Gram-negative and three Gram-positive bacterial strains. Our results indicate that none of the three new lactoferrin fragments have antimicrobial properties for the bacteria tested, but hLF 1-11 was lethal against Pseudomonas aeruginosa. The addition of serine protease inhibitors with the hLF fragments did not enhance their activity, except for hLF 1-11 against P. aeruginosa, which MIC dropped from 128 to 64 µg/mL. Furthermore, we investigated the impact of EDTA with/without serine protease inhibitors and the hLF peptides on selected bacteria. We stress the importance of reporting non-AMP sequences for the development of next-generation AMP prediction models, which suffer from the lack of experimentally validated negative dataset for training and benchmarking.

Testing Antimicrobial Properties of Selected Short Amyloids.

Amyloids and antimicrobial peptides (AMPs) have many similarities, e.g., both kill microorganisms by destroying their membranes, form aggregates, and modulate the innate immune system. Given these similarities and the fact that the antimicrobial properties of short amyloids have not yet been investigated, we chose a group of potentially antimicrobial short amyloids to verify their impact on bacterial and eukaryotic cells. We used AmpGram, a best-performing AMP classification model, and selected ten amyloids with the highest AMP probability for our experimental research. Our results indicate that four tested amyloids: VQIVCK, VCIVYK, KCWCFT, and GGYLLG, formed aggregates under the conditions routinely used to evaluate peptide antimicrobial properties, but none of the tested amyloids exhibited antimicrobial or cytotoxic properties. Accordingly, they should be included in the negative datasets to train the next-generation AMP prediction models, based on experimentally confirmed AMP and non-AMP sequences. In the article, we also emphasize the importance of reporting non-AMPs, given that only a handful of such sequences have been officially confirmed.

Proteomic Screening for Prediction and Design of Antimicrobial Peptides with AmpGram.

Antimicrobial peptides (AMPs) are molecules widespread in all branches of the tree of life that participate in host defense and/or microbial competition. Due to their positive charge, hydrophobicity and amphipathicity, they preferentially disrupt negatively charged bacterial membranes. AMPs are considered an important alternative to traditional antibiotics, especially at the time when multidrug-resistant bacteria being on the rise. Therefore, to reduce the costs of experimental research, robust computational tools for AMP prediction and identification of the best AMP candidates are essential. AmpGram is our novel tool for AMP prediction; it outperforms top-ranking AMP classifiers, including AMPScanner, CAMPR3R and iAMPpred. It is the first AMP prediction tool created for longer AMPs and for high-throughput proteomic screening. AmpGram prediction reliability was confirmed on the example of lactoferrin and thrombin. The former is a well known antimicrobial protein and the latter a cryptic one. Both proteins produce (after protease treatment) functional AMPs that have been experimentally validated at molecular level. The lactoferrin and thrombin AMPs were located in the antimicrobial regions clearly detected by AmpGram. Moreover, AmpGram also provides a list of shot 10 amino acid fragments in the antimicrobial regions, along with their probability predictions; these can be used for further studies and the rational design of new AMPs. AmpGram is available as a web-server, and an easy-to-use R package for proteomic analysis at CRAN repository.

Many alternative and theoretical genetic codes are more robust to amino acid replacements than the standard genetic code.

We evaluated the differences between the standard genetic code (SGC) and its known alternative variants in terms of the consequences of amino acids replacements. Furthermore, the properties of all the possible theoretical genetic codes, which differ from the SGC by one, two or three changes in codon assignments were also tested. Although the SGC is closer to the best theoretical codes than to the worst ones due to the minimization of amino acid replacements, from 10% to 27% of the all possible theoretical codes minimize the effect of these replacements better than the SGC. Interestingly, many types of codon reassignments observed in the alternative codes are also responsible for the substantial robustness to amino acid replacements. As many as 18 out of 21 alternatives perform better than the SGC under the assumed optimization criteria. These findings suggest that not all reassignments in the alternative codes are neutral and some of them could be selected to reduce harmful effects of mutations or translation of protein-coding sequences. The results also imply that the standard genetic code can be improved in this respect by a quite small number of changes, which are in fact realized in its variants. It would mean that the tendency to minimize mutational errors was not the main force that drove the evolution of the SGC.

Prediction of Signal Peptides in Proteins from Malaria Parasites.

Signal peptides are N-terminal presequences responsible for targeting proteins to the endomembrane system, and subsequent subcellular or extracellular compartments, and consequently condition their proper function. The significance of signal peptides stimulates development of new computational methods for their detection. These methods employ learning systems trained on datasets comprising signal peptides from different types of proteins and taxonomic groups. As a result, the accuracy of predictions are high in the case of signal peptides that are well-represented in databases, but might be low in other, atypical cases. Such atypical signal peptides are present in proteins found in apicomplexan parasites, causative agents of malaria and toxoplasmosis. Apicomplexan proteins have a unique amino acid composition due to their AT-biased genomes. Therefore, we designed a new, more flexible and universal probabilistic model for recognition of atypical eukaryotic signal peptides. Our approach called signalHsmm includes knowledge about the structure of signal peptides and physicochemical properties of amino acids. It is able to recognize signal peptides from the malaria parasites and related species more accurately than popular programs. Moreover, it is still universal enough to provide prediction of other signal peptides on par with the best preforming predictors.

Cymbomonas tetramitiformis - a peculiar prasinophyte with a taste for bacteria sheds light on plastid evolution.

Cymbomonas tetramitiformis is a peculiar green alga that unites in one cell the abilities of photosynthesis and phagocytosis, which makes it a very useful model for the study of the evolution of plastid endosymbiosis. We have pondered over this issue and propose an evolutionary scenario of trophic strategies in eukaryotes, including primary and secondary plastid endosymbioses. C. tetramitiformis is a prototroph, just like the common ancestor of Archaeplastida was, and can synthesize most small organic molecules contrary to other eukaryotic phagotrophs, e.g. some metazoans, amoebozoans, and ciliates, which have not evolved tight endosymbiotic relationships. In order to establish a permanent photosynthetic endosymbiont they do not have to become prototrophs, but have to acquire the genes necessary for plastid retention via horizontal (including endosymbiotic) gene transfer. Such processes occurred successfully in the ancestors of eukaryotes with permanent secondary plastids and thus led to their great diversification. The preservation of phagocytosis in Cymbomonas (and some other prasinophytes as well) seems to result from nutrient deficiency in their oligotrophic habitats. This forces them to supplement their diet with phagocytized prey, in contrasts to the thecate amoeba Paulinella chromatophora, which also successfully transformed cyanobacteria into permanent organelles. Although Paulinella endosymbionts were acquired very recently in comparison to primary plastids, Paulinella has lost the ability to phagocytose, most probably due to the fact that it inhabits nutrient-rich environments, which renders the phagotrophy nonessential.

Characterization of signal and transit peptides based on motif composition and taxon-specific patterns.

Targeting peptides or presequences are N-terminal extensions of proteins that encode information about their cellular localization. They include signal peptides (SP), which target proteins to the endoplasmic reticulum, and transit peptides (TP) directing proteins to the organelles of endosymbiotic origin: chloroplasts and mitochondria. TPs were hypothesized to have evolved from antimicrobial peptides (AMPs), which are responsible for the host defence against microorganisms, including bacteria, fungi and viruses. In this study, we performed comprehensive bioinformatic analyses of amino acid motifs of targeting peptides and AMPs using a curated set of experimentally verified proteins. We identified motifs frequently occurring in each type of presequence showing specific patterns associated with their amino acid composition, and investigated their position within the presequence. We also compared motif patterns among different taxonomic groups and identified taxon-specific features, providing some evolutionary insights. Considering the functional relevance and many practical applications of targeting peptides and AMPs, we believe that our analyses will prove useful for their design, and better understanding of protein import mechanism and presequence evolution.

Prediction of protein subplastid localization and origin with PlastoGram.

Due to their complex history, plastids possess proteins encoded in the nuclear and plastid genome. Moreover, these proteins localize to various subplastid compartments. Since protein localization is associated with its function, prediction of subplastid localization is one of the most important steps in plastid protein annotation, providing insight into their potential function. Therefore, we create a novel manually curated data set of plastid proteins and build an ensemble model for prediction of protein subplastid localization. Moreover, we discuss problems associated with the task, e.g. data set sizes and homology reduction. PlastoGram classifies proteins as nuclear- or plastid-encoded and predicts their localization considering: envelope, stroma, thylakoid membrane or thylakoid lumen; for the latter, the import pathway is also predicted. We also provide an additional function to differentiate nuclear-encoded inner and outer membrane proteins. PlastoGram is available as a web server at https://biogenies.info/PlastoGram and as an R package at https://github.com/BioGenies/PlastoGram . The code used for described analyses is available at https://github.com/BioGenies/PlastoGram-analysis .

Protein import into the photosynthetic organelles of Paulinella chromatophora and its implications for primary plastid endosymbiosis.

The rhizarian amoeba Paulinella chromatophora harbors two photosynthetically active organelles of cyanobacterial origin that have been acquired independently of classic primary plastids. Because their acquisition did take place relatively recently, they are expected to provide new insight into the ancient cyanobacterial primary endosymbiosis. During the process of Paulinella endosymbiont-to-organelle transformation, more than 30 genes have been transferred from the organelle to the host nuclear genome via endosymbiotic gene transfer (EGT). The article discusses step-by-step protein import of EGT-derived proteins into Paulinella photosynthetic organelles with the emphasis on the nature of their targeting signals and the final passage of proteins through the inner organelle membrane. The latter most probably involves a simplified Tic translocon composed of Tic21- and Tic32-like proteins as well as a Hsp70-based motor responsible for pulling of imported proteins into the organelle matrix. Our results indicate that although protein translocation across the inner membrane of Paulinella photosynthetic organelles seems to resemble the one in classic primary plastids, the transport through the outer membrane does not. The differences could result from distinct integration pathways of Paulinella photosynthetic organelles and primary plastids with their respective host cells.

The Photosynthetic Adventure of Paulinella Spp.

Paulinella photosynthetic species are unicellular, silica shell-forming amoebas classified into the supergroup Rhizaria. They crawl at the bottom of freshwater and brackish environments with the help of filose pseudopodia. These protists have drawn the attention of the scientific community because of two photosynthetic bodies, called chromatophores, that fill up their cells permitting fully photoautotrophic existence. Paulinella chromatophores, similarly to primary plastids of the Archaeplastida supergroup (including glaucophytes, red algae as well as green algae and land plants), evolved from free-living cyanobacteria in the process of endosymbiosis. Interestingly, these both cyanobacterial acquisitions occurred independently, thereby undermining the paradigm of the rarity of endosymbiotic events. Chromatophores were derived from α-cyanobacteria relatively recently 60-140 million years ago, whereas primary plastids originated from ß-cyanobacteria more than 1.5 billion years ago. Since their acquisition, chromatophore genomes have undergone substantial reduction but not to the extent of primary plastid genomes. Consequently, they have also developed mechanisms for transport of metabolites and nuclear-encoded proteins along with appropriate targeting signals. Therefore, chromatophores of Paulinella photosynthetic species, similarly to primary plastids, are true cellular organelles. They not only show that endosymbiotic events might not be so rare but also make a perfect model for studying the process of organellogenesis. In this chapter, we summarize the current knowledge and retrace the fascinating adventure of Paulinella species on their way to become photoautotrophic organisms.

CancerGram: An Effective Classifier for Differentiating Anticancer from Antimicrobial Peptides.

Antimicrobial peptides (AMPs) constitute a diverse group of bioactive molecules that provide multicellular organisms with protection against microorganisms, and microorganisms with weaponry for competition. Some AMPs can target cancer cells; thus, they are called anticancer peptides (ACPs). Due to their small size, positive charge, hydrophobicity and amphipathicity, AMPs and ACPs interact with negatively charged components of biological membranes. AMPs preferentially permeabilize microbial membranes, but ACPs additionally target mitochondrial and plasma membranes of cancer cells. The preference towards mitochondrial membranes is explained by their membrane potential, membrane composition resulting from α-proteobacterial origin and the fact that mitochondrial targeting signals could have evolved from AMPs. Taking into account the therapeutic potential of ACPs and millions of deaths due to cancer annually, it is of vital importance to find new cationic peptides that selectively destroy cancer cells. Therefore, to reduce the costs of experimental research, we have created a robust computational tool, CancerGram, that uses n-grams and random forests for predicting ACPs. Compared to other ACP classifiers, CancerGram is the first three-class model that effectively classifies peptides into: ACPs, AMPs and non-ACPs/non-AMPs, with AU1U amounting to 0.89 and a Kappa statistic of 0.65. CancerGram is available as a web server and R package on GitHub.

PhyMet2 : a database and toolkit for phylogenetic and metabolic analyses of methanogens.

The vast biodiversity of the microbial world and how little is known about it, has already been revealed by extensive metagenomics analyses. Our rudimentary knowledge of microbes stems from difficulties concerning their isolation and culture in laboratory conditions, which is necessary for describing their phenotype, among other things, for biotechnological purposes. An important component of the understudied ecosystems is methanogens, archaea producing a potent greenhouse-effect gas methane. Therefore, we created PhyMet2 , the first database that combines descriptions of methanogens and their culturing conditions with genetic information. The database contains a set of utilities that facilitate interactive data browsing, data comparison, phylogeny exploration and searching for sequence homologues. The most unique feature of the database is the web server MethanoGram, which can be used to significantly reduce the time and cost of searching for the optimal culturing conditions of methanogens by predicting them based on 16S RNA sequences. The database will aid many researchers in exploring the world of methanogens and their applications in biotechnological processes. PhyMet2 with the MethanoGram predictor is available at http://metanogen.biotech.uni.wroc.pl.

Peculiarities within peculiarities - dinoflagellates and their mitochondrial genomes.

After the establishment of an endosymbiotic relationship between a proto-mitochondrion and its probable archaeal host, mitochondrial genomes underwent a spectacular reductive evolution. An interesting pathway was chosen by mitogenomes of unicellular protists called dinoflagellates, which experienced an additional wave of reduction followed by amplification and rearrangement leading to their secondary complexity. The former resulted in a mitogenome consisting of only three protein-coding genes, the latter in their multiple copies being scattered across numerous chromosomes and the evolution of complex processes for their expression. These stunning features raise a question about the future of the dinoflagellate mitochondrial genome.

Evolutionary history and phylogeographic relationships of shrews from Sorex araneus group.

Shrews of the Sorex genus are an evolutionarily successful group that includes more than 77 species widely distributed in Eurasia and North America. The genus is one of the rare cases where karyotypic changes reflect well the evolutionary relationships among its species. The taxa showing the greatest variation in karyotype are usually classified into the Sorex araneus group. Its evolution was associated with chromosomal rearrangements, which could have promoted fast diversification of this group into many chromosomal races and species. These processes were additionally complicated by introgressions of mitochondrial DNA, which made the evolutionary history of this group quite complex and difficult to infer. To tackle the problem, we performed multi-method phylogenetic analyses based on mitochondrial cytochrome b that is considered a good molecular marker available for many representatives of Sorex. The results were compared with phylogenies based on chromosomal rearrangement data and put into temporal and spatial context using molecular dating and historical biogeography methods. We complemented the study with the estimation of diversification rates within the S. araneus group as well as comparing the results with paleontological records and climatic oscillations within the last 4 million years. Based on the gathered data, we proposed a hypothetical scenario for the evolution and geographic dispersion of species belonging to the S. araneus group. The shrews began to diversify about 2.7 million years ago in Eurasia and then migrated at least twice to North America. The evolution of shrews was driven by Pleistocene glacial and interglacial cycles, which increased their speciation rate and the emergence of new lineages. The migrations of populations were accompanied by introgressions of mitochondrial DNA into native shrews and occurred at least twice.

How protein targeting to primary plastids via the endomembrane system could have evolved? A new hypothesis based on phylogenetic studies.

BACKGROUND: It is commonly assumed that a heterotrophic ancestor of the supergroup Archaeplastida/Plantae engulfed a cyanobacterium that was transformed into a primary plastid; however, it is still unclear how nuclear-encoded proteins initially were imported into the new organelle. Most proteins targeted to primary plastids carry a transit peptide and are transported post-translationally using Toc and Tic translocons. There are, however, several proteins with N-terminal signal peptides that are directed to higher plant plastids in vesicles derived from the endomembrane system (ES). The existence of these proteins inspired a hypothesis that all nuclear-encoded, plastid-targeted proteins initially carried signal peptides and were targeted to the ancestral primary plastid via the host ES. RESULTS: We present the first phylogenetic analyses of Arabidopsis thaliana α-carbonic anhydrase (CAH1), Oryza sativa nucleotide pyrophosphatase/phosphodiesterase (NPP1), and two O. sativa α-amylases (αAmy3, αAmy7), proteins that are directed to higher plant primary plastids via the ES. We also investigated protein disulfide isomerase (RB60) from the green alga Chlamydomonas reinhardtii because of its peculiar dual post- and co-translational targeting to both the plastid and ES. Our analyses show that these proteins all are of eukaryotic rather than cyanobacterial origin, and that their non-plastid homologs are equipped with signal peptides responsible for co-translational import into the host ES. Our results indicate that vesicular trafficking of proteins to primary plastids evolved long after the cyanobacterial endosymbiosis (possibly only in higher plants) to permit their glycosylation and/or transport to more than one cellular compartment. CONCLUSIONS: The proteins we analyzed are not relics of ES-mediated protein targeting to the ancestral primary plastid. Available data indicate that Toc- and Tic-based translocation dominated protein import into primary plastids from the beginning. Only a handful of host proteins, which already were targeted through the ES, later were adapted to reach the plastid via the vesicular trafficking. They represent a derived class of higher plant plastid-targeted proteins with an unusual evolutionary history.

Possible import routes of proteins into the cyanobacterial endosymbionts/plastids of Paulinella chromatophora.

The rhizarian amoeba Paulinella chromatophora harbors two photosynthetically active and deeply integrated cyanobacterial endosymbionts acquired ~60 million years ago. Recent genomic analyses of P. chromatophora have revealed the loss of many essential genes from the endosymbiont's genome, and have identified more than 30 genes that have been transferred to the host cell's nucleus through endosymbiotic gene transfer (EGT). This indicates that, similar to classical primary plastids, Paulinella endosymbionts have evolved a transport system to import their nuclear-encoded proteins. To deduce how these proteins are transported, we searched for potential targeting signals in genes for 10 EGT-derived proteins. Our analyses indicate that five proteins carry potential signal peptides, implying they are targeted via the host endomembrane system. One sequence encodes a mitochondrial-like transit peptide, which suggests an import pathway involving a channel protein residing in the outer membrane of the endosymbiont. No N-terminal targeting signals were identified in the four other genes, but their encoded proteins could utilize non-classical targeting signals contained internally or in C-terminal regions. Several amino acids more often found in the Paulinella EGT-derived proteins than in their ancestral set (proteins still encoded in the endosymbiont genome) could constitute such signals. Characteristic features of the EGT-derived proteins are low molecular weight and nearly neutral charge, which both could be adaptations to enhance passage through the peptidoglycan wall present in the intermembrane space of the endosymbiont's envelope. Our results suggest that Paulinella endosymbionts/plastids have evolved several different import routes, as has been shown in classical primary plastids.

Organelle evolution: Paulinella breaks a paradigm.

It is commonly assumed that transformations of endosymbionts into organelles are exceptionally rare evolutionary events because of hypothetical difficulties in the origin of an import apparatus for nuclear-encoded, organelle-targeted proteins along with their targeting signals. A challenge to this view comes from recent studies of protein import into the cyanobacterial endosymbionts/organelles of Paulinella chromatophora.

Identification of new in vivo phosphosites on lamin Dm - the evidence of heterogeneity of phosphorylation sites in different Drosophila tissues.

Changes in the nuclear structure and function during the cell cycle are thought to be correlated with lamins phosphorylation. Here, we report the identification of new in vivo phosphorylation sites on Drosophila melanogater lamin Dm using immunoisolation and mass spectrometry with collision-induced peptide fragmentation (Electrospray-Linear Trap Quadrupole- Fourier Transform Ion Cyclotron Resonance MS/MS). We identified S19 and confirmed previously suggested S595 as phosphorylated amino acid residues on embryonic lamin Dm. We also found that T597 is phosphorylated in vivo in cultured Kc cells while S595 in embryos, which suggests that different neighboring phosphoacceptors may be modified within the same region. We demonstrate also that Drosophila melanogaster lamin Dm in very early (syncytial) embryos is almost completely dispersed through the entire embryo. Only fraction of lamin Dm is associated with nuclei and nuclear envelopes. In later stages, due to the synchronization of mitosis, lamin Dm may be both nuclear and cytoplasmic in the same embryo. Our results provide a new and essential data for better understanding of the lamin phosporylation in development and cell cycle regulation in Drosophila.