Nullomer derived anticancer peptides (NulloPs): differential lethal effects on normal and cancer cells in vitro

A survey of k-mer methods and applications in bioinformatics

The rapid progression of genomics and proteomics has been driven by the advent of advanced sequencing technologies, large, diverse, and readily available omics datasets, and the evolution of computational data processing capabilities. The vast amount of data generated by these advancements necessitates efficient algorithms to extract meaningful information. K-mers serve as a valuable tool when working with large sequencing datasets, offering several advantages in computational speed and memory efficiency and carrying the potential for intrinsic biological functionality. This review provides an overview of the methods, applications, and significance of k-mers in genomic and proteomic data analyses, as well as the utility of absent sequences, including nullomers and nullpeptides, in disease detection, vaccine development, therapeutics, and forensic science. Therefore, the review highlights the pivotal role of k-mers in addressing current genomic and proteomic problems and underscores their potential for future breakthroughs in research.

kmerDB: A database encompassing the set of genomic and proteomic sequence information for each species

The decrease in sequencing expenses has facilitated the creation of reference genomes and proteomes for an expanding array of organisms. Nevertheless, no established repository that details organism-specific genomic and proteomic sequences of specific lengths, referred to as kmers, exists to our knowledge. In this article, we present kmerDB, a database accessible through an interactive web interface that provides kmer-based information from genomic and proteomic sequences in a systematic way. kmerDB currently contains 202,340,859,107 base pairs and 19,304,903,356 amino acids, spanning 54,039 and 21,865 reference genomes and proteomes, respectively, as well as 6,905,362 and 149,305,183 genomic and proteomic species-specific sequences, termed quasi-primes. Additionally, we provide access to 5,186,757 nucleic and 214,904,089 peptide sequences absent from every genome and proteome, termed primes. kmerDB features a user-friendly interface offering various search options and filters for easy parsing and searching. The service is available at: www.kmerdb.com.

Peptide absent sequences emerging in human cancers

Early diagnosis of cancer can significantly improve survival of cancer patients; however sensitive and highly specific biomarkers for cancer detection are currently lacking for most cancer types. Nullpeptides are short peptides that are absent from the human proteome. Here, we examined the emergence of nullpeptides during cancer development. We analyzed 3,600,964 somatic mutations across 10,064 whole exome sequencing tumor samples spanning 32 cancer types. We analyze RNA-seq data from primary tumor samples to identify the subset of nullpeptides that emerge in highly expresed genes. We show that nullpeptides, and particularly the subset that is highly recurrent across cancer patients, can be identified in tumor biopsy samples. We find that cancer genes show an excess of nullpeptides and detect nullpeptide hotspots in specific loci of oncogenes and tumor suppressors. We also observe that recurrent nullpeptides are more likely to be found in neoantigens, which have been shown to be effective targets for immunotherapy, suggesting that they can be used to prioritize candidates. Our findings provide evidence for the utility of nullpeptides as cancer detection and therapeutic biomarkers.

9S1R nullomer peptide induces mitochondrial pathology, metabolic suppression, and enhanced immune cell infiltration, in triple-negative breast cancer mouse model

Nullomers are the shortest strings of absent amino acid (aa) sequences in a species or group of species. Primes are those nullomers that have not been detected in the genome of any species. 9S1R is a 5-aa peptide prime sequence attached to 5-arginine aa, used to treat triple negative breast cancer (TNBC) in an in vivo mouse model. This unique peptide, administered with a trehalose carrier (9S1R-NulloPT), offers enhanced solubility and exhibits distinct anti-cancer effects against TNBC. In our study, we investigated the effect of 9S1R-NulloPT on tumor growth, metabolism, metastatic burden, tumor immune-microenvironment (TME), and transcriptome of aggressive mouse TNBC tumors. Notably, treated mice had smaller tumors in the initial phase of the treatment, as compared to untreated control, and diminished in vivo and ex vivo bioluminescence at later-stages - indicative of metabolically quiescent, dying tumors. The treatment also caused changes in TME with increased infiltration of immune cells and altered tumor transcriptome, with 365 upregulated genes and 710 downregulated genes. Consistent with in vitro data, downregulated genes were enriched in cellular metabolic processes (179), specifically mitochondrial TCA cycle/oxidative phosphorylation (44), and translation machinery/ribosome biogenesis (45). The upregulated genes were associated with the developmental (13), ECM organization (12) and focal adhesion pathways (7). In conclusion, our study demonstrates that 9S1R-NulloPT effectively reduced tumor growth during its initial phase, altering the TME and tumor transcriptome. The treatment induced mitochondrial pathology which led to a metabolic deceleration in tumors, aligning with in vitro observations.

Nullomer peptide increases immune cell infiltration and reduces tumor metabolism in triple negative breast cancer mouse model

Background

Nullomers are the shortest strings of absent amino acid (aa) sequences in a species or group of species. Primes are those nullomers that have not been detected in the genome of any species. 9S1R is a 5-aa peptide derived from a prime sequence that is tagged with 5 arginine aa, used to treat triple negative breast cancer (TNBC) in an in vivo TNBC mouse model. 9S1R is administered in trehalose (9S1R-NulloPT), which enhances solubility and exhibits some independent effects against tumor growth and is thus an important component in the drug preparation.

Method

We examined the effect of 9S1R-NulloPT on tumor growth, metabolism, metastatic burden, necrosis, tumor immune microenvironment, and the transcriptome of aggressive mouse TNBC tumors.

Results

The peptide-treated mice had smaller tumors in the initial phase of the treatment, as compared to the untreated control, and reduced in vivo bioluminescence at later stages, which is indicative of metabolically inactive tumors. A decrease in ex vivo bioluminescence was also observed in the excised tumors of treated mice, but not in the secondary metastasis in the lungs. The treatment also caused changes in tumor immune microenvironment with increased infiltration of immune cells and margin inflammation. The treatment upregulated 365 genes and downregulated 710 genes in tumors compared to the untreated group. Consistent with in vitro findings in breast cancer cell lines, downregulated genes in the treated TNBC tumors include Cellular Metabolic Process Related genes (179), specifically mitochondrial genes associated with TCA cycle/oxidative phosphorylation (44), and translation machinery/ribosome biogenesis genes (45). Among upregulated genes, the Developmental Pathway (13), ECM Organization (12) and Focal Adhesion Related Pathways (7) were noteworthy. We also present data from a pilot study using a bilateral BC mouse model, which supports our findings.

Conclusion

In conclusion, although 9S1R-NulloPT was moderate at reducing the tumor volume, it altered the tumor immune microenvironment as well as the tumor transcriptome, rendering tumors metabolically less active by downregulating the mitochondrial function and ribosome biogenesis. This corroborates previously published in vitro findings.

An immunological glimpse of human virus peptides: distance from self, MHC class I binding, Proteasome Cleveage, TAP Transport and sequence composition entropy

Adaptive immune response is triggered when specific pathogen peptides called epitopes are recognised as exogenous according to the paradigm of self/non-self. To be recognized by immune cells, epitopes have to be exposed (presented) on the surface of the cell. Predicting if a peptide is exposed is important to shed light on the rules that govern immune response, and thus to identify potential targets, and to design vaccine and drugs. We focused on peptides exposed on cell surface and made accessible to immune system through the MHC Class I complex. Before this can happen, three successive selection steps have to take place: a) Proteasome cleveage, b) TAP Transport, and c) binding to MHC-class I. Starting from a set of 211 host human reference viruses, we computed the set of unique peptides occurring in the correspondent proteomes. Then, we obtained the probability values of Proteasome Cleveage, TAP Transport and Binding to MHC Class I associated to those peptides through established prediction software tools. Such values were analysed in conjunction with two other features that could play a major role: the distance from self, strictly linked to the concept of nullomers, and the sequence entropy, measuring the complexity of the peptide amino acid composition. The analysis confirmed and extended previous results on a larger, more significant and consistent data set; we showed that the higher the distances from self, the higher the score of TAP Transport and binding to MHC class I; no significant association was instead found between distance from self and Proteasome Cleveage. Additionally, amino acid peptide composition entropy was significantly associated with the other features. In particular, higher entropies were linked with higher scores of Proteasome Cleveage, TAP Transport, Binding to MHC Class I, and higher distance from self. The relationship among the three selection steps provided evidence of a tight correlation among them, clearly suggesting it could be the product of a co-evolutive process. We believe that these results give new insights on the complex processes that regulate peptide presentation through MHC class I, and unveil the mechanisms the allow the immune system to distinguish self and viral non-self peptides.

Absent from DNA and protein: genomic characterization of nullomers and nullpeptides across functional categories and evolution

Nullomers and nullpeptides are short DNA or amino acid sequences that are absent from a genome or proteome, respectively. One potential cause for their absence could be their having a detrimental impact on an organism. RESULTS: Here, we identify all possible nullomers and nullpeptides in the genomes and proteomes of thirty eukaryotes and demonstrate that a significant proportion of these sequences are under negative selection. We also identify nullomers that are unique to specific functional categories: coding sequences, exons, introns, 5'UTR, 3'UTR, promoters, and show that coding sequence and promoter nullomers are most likely to be selected against. By analyzing all protein sequences across the tree of life, we further identify 36,081 peptides up to six amino acids in length that do not exist in any known organism, termed primes. We next characterize all possible single base pair mutations that can lead to the appearance of a nullomer in the human genome, observing a significantly higher number of mutations than expected by chance for specific nullomer sequences in transposable elements, likely due to their suppression. We also annotate nullomers that appear due to naturally occurring variants and show that a subset of them can be used to distinguish between different human populations. Analysis of nullomers and nullpeptides across vertebrate evolution shows they can also be used as phylogenetic classifiers. CONCLUSIONS: We provide a catalog of nullomers and nullpeptides in distinct functional categories, develop methods to systematically study them, and highlight the use of variability in these sequences in other analyses.

Significant non-existence of sequences in genomes and proteomes

Minimal absent words (MAWs) are minimal-length oligomers absent from a genome or proteome. Although some artificially synthesized MAWs have deleterious effects, there is still a lack of a strategy for the classification of non-occurring sequences as potentially malicious or benign. In this work, by using Markovian models with multiple-testing correction, we reveal significant absent oligomers, which are statistically expected to exist. This suggests that their absence is due to negative selection. We survey genomes and proteomes covering the diversity of life and find thousands of significant absent sequences. Common significant MAWs are often mono- or dinucleotide tracts, or palindromic. Significant viral MAWs are often restriction sites and may indicate unknown restriction motifs. Surprisingly, significant mammal genome MAWs are often present, but rare, in other mammals, suggesting that they are suppressed but not completely forbidden. Significant human MAWs are frequently present in prokaryotes, suggesting immune function, but rarely present in human viruses, indicating viral mimicry of the host. More than one-fourth of human proteins are one substitution away from containing a significant MAW, with the majority of replacements being predicted harmful. We provide a web-based, interactive database of significant MAWs across genomes and proteomes.

The farther the better: Investigating how distance from human self affects the propensity of a peptide to be presented on cell surface by MHC class I molecules, the case of Trypanosoma cruzi

More than twenty years ago the reverse vaccinology paradigm came to light trying to design new vaccines based on the analysis of genomic information in order to select those pathogen peptides able to trigger an immune response. In this context, focusing on the proteome of Trypanosoma cruzi, we investigated the link between the probabilities for pathogen peptides to be presented on a cell surface and their distance from human self. We found a reasonable but, as far as we know, undiscovered property: the farther the distance between a peptide and the human-self the higher the probability for that peptide to be presented on a cell surface. We also found that the most distant peptides from human self bind, on average, a broader collection of HLAs than expected, implying a potential immunological role in a large portion of individuals. Finally, introducing a novel quantitative indicator for a peptide to measure its potential immunological role, we proposed a pool of peptides that could be potential epitopes and that can be suitable for experimental testing. The software to compute peptide classes according to the distance from human self is free available at http://www.iasi.cnr.it/~dsantoni/nullomers.

Global pentapeptide statistics are far away from expected distributions

The relationships between polypeptide composition, sequence, structure and function have been puzzling biologists ever since first protein sequences were determined. Here, we study the statistics of occurrence of all possible pentapeptide sequences in known proteins. To compensate for the non-uniform distribution of individual amino acid residues in protein sequences, we investigate separately all possible permutations of every given amino acid composition. For the majority of permutation groups we find that pentapeptide occurrences deviate strongly from the expected binomial distributions, and that the observed distributions are also characterized by high numbers of outlier sequences. An analysis of identified outliers shows they often contain known motifs and rare amino acids, suggesting that they represent important functional elements. We further compare the pentapeptide composition of regions known to correspond to protein domains with that of non-domain regions. We find that a substantial number of pentapeptides is clearly strongly favored in protein domains. Finally, we show that over-represented pentapeptides are significantly related to known functional motifs and to predicted ancient structural peptides.

Viral peptides-MHC interaction: Binding probability and distance from human peptides

Identification of peptides binding to MHC class I complex can play a crucial role in retrieving potential targets able to trigger an immune response. Affinity binding of viral peptides can be estimated through effective computational methods that in the most of cases are based on machine learning approach. Achieving a better insight into peptide features that impact on the affinity binding rate is a challenging issue. In the present work we focused on 9-mer peptides of Human immunodeficiency virus type 1 and Human herpes simplex virus 1, studying their binding to MHC class I. Viral 9-mers were partitioned into different classes, where each class is characterized by how far (in terms of mutation steps) the peptides belonging to that class are from human 9-mers. Viral 9-mers were partitioned in different classes, based on the number of mutation steps they are far from human 9-mers. We showed that the overall binding probability significantly differs among classes, and it typically increases as the distance, computed in terms of number of mutation steps from the human set of 9-mers, increases. The binding probability is particularly high when considering viral 9-mers that are far from all human 9-mers more than three mutation steps. A further evidence, providing significance to those special viral peptides and suggesting a potential role they can play, comes from the analysis of their distribution along viral genomes, as it revealed they are not randomly located, but they preferentially occur in specific genes.

Tools to Measure Cell Health and Cytotoxicity Using High Content Imaging and Analysis

High content screening (HCS)-based multiparametric measurements are very useful in early toxicity testing and safety assessment during drug development, and useful in evaluating the impact from new food supplements and environmental toxicants. Mitochondrial membrane potential, plasma membrane permeability, oxidative stress, phosphoplipidosis, and steatosis are a few of the important markers routinely studied for the assessment of drug-induced liver injury and toxicity. Mitochondrial dysfunction leads to oxidative stress and cell death. Liver injury from drug-induced phospholipidosis and steatosis is routinely studied in hepatotoxicity investigations to determine the risk factors and fate of drugs or chemical compounds as some drugs can lead to defects in lipid metabolism and accumulation of lipids in lysosomes. In this chapter, we describe fluorescent reagents and the protocols for the measurement of various parameters such as mitochondrial membrane potential, plasma membrane permeability, oxidative stress, phospholipidosis, and steatosis using high content imaging-based methodologies and instrumentation.

The effect of Nullomer-derived peptides 9R, 9S1R and 124R on the NCI-60 panel and normal cell lines

BACKGROUND

Nullomer peptides are the smallest sequences absent from databases of natural proteins. We first began compiling a list of absent 5-amino acid strings in 2006 (1). We report here the effects of Nullomer-derived peptides 9R, 9S1R and 124R on the NCI-60 panel, derived from human cancers of 9 organs (kidney, ovary, skin melanoma, lung, brain, lung, colon, prostate and the hematopoietic system), and four normal cell lines (endothelial HUVEC, skin fibroblasts BJ, colon epithelial FHC and normal prostate RWPE-1).

METHODS

NCI-60 cancer cell panel and four normal cell lines were cultured in vitro in RPMI1640 supplemented with 10% Hyclone fetal bovine serum and exposed for 48 h to 5 μM, 25 μM and 50 μM of peptides 9R, 9S1R and 124R. Viability was assessed by CCK-8 assay. For peptide ATP depletion effects, one cell line representing each organ in the NCI-60 panel, and four normal cell lines were exposed to 50 μM of peptides 9R, 9S1R and 124R for 3 h. The ATP content was assessed in whole cells, and their supernatants.

RESULTS

Peptides 9S1R and 9R are respectively lethal to 95 and 81.6% of the 60 cancer cell lines tested. Control peptide 124R has no effect on the growth of these cells. Especially interesting the fact that peptides 9R and 9S1R are capable of killing drug-resistant and hormone-resistant cell lines, and even cancer stem cells. Peptides 9R and 9S1R have a broader activity spectrum than many cancer drugs in current use, can completely deplete cellular ATP within 3 h, and are less toxic to 3 of the 4 normal cell lines tested than they are to several cancers.

CONCLUSIONS

Nullomer peptides 9R and 9S1R have a large broad lethal effect on cancer cell lines derived from nine organs represented in the NCI-60 panel. This broad activity crosses many of the categorical divisions used in the general classification of cancers: solid vs liquid cancers, drug sensitive vs drug resistant, hormone sensitive vs hormone resistant, cytokine sensitive vs cytokine non sensitive, slow growing vs rapid growing, differentiated vs dedifferentiated cancers. Furthermore peptides 9R and 9S1R are lethal to cancer stem cells and breast canrcinosarcoma.

Nullomers and High Order Nullomers in Genomic Sequences

A nullomer is an oligomer that does not occur as a subsequence in a given DNA sequence, i.e. it is an absent word of that sequence. The importance of nullomers in several applications, from drug discovery to forensic practice, is now debated in the literature. Here, we investigated the nature of nullomers, whether their absence in genomes has just a statistical explanation or it is a peculiar feature of genomic sequences. We introduced an extension of the notion of nullomer, namely high order nullomers, which are nullomers whose mutated sequences are still nullomers. We studied different aspects of them: comparison with nullomers of random sequences, CpG distribution and mean helical rise. In agreement with previous results we found that the number of nullomers in the human genome is much larger than expected by chance. Nevertheless antithetical results were found when considering a random DNA sequence preserving dinucleotide frequencies. The analysis of CpG frequencies in nullomers and high order nullomers revealed, as expected, a high CpG content but it also highlighted a strong dependence of CpG frequencies on the dinucleotide position, suggesting that nullomers have their own peculiar structure and are not simply sequences whose CpG frequency is biased. Furthermore, phylogenetic trees were built on eleven species based on both the similarities between the dinucleotide frequencies and the number of nullomers two species share, showing that nullomers are fairly conserved among close species. Finally the study of mean helical rise of nullomers sequences revealed significantly high mean rise values, reinforcing the hypothesis that those sequences have some peculiar structural features. The obtained results show that nullomers are the consequence of the peculiar structure of DNA (also including biased CpG frequency and CpGs islands), so that the hypermutability model, also taking into account CpG islands, seems to be not sufficient to explain nullomer phenomenon. Finally, high order nullomers could emphasize those features that already make simple nullomers useful in several applications.

Safeguarding forensic DNA reference samples with nullomer barcodes

Unintended transfer of biological material containing DNA is a concern to all laboratories conducting PCR analysis. While forensic laboratories have protocols in place to reduce the possibility of contaminating casework samples, there is no way to detect when a reference sample is mislabeled as evidence, or contaminates a forensic sample. Thus there is public concern regarding the safeguarding of DNA submitted to crime labs. We demonstrate a method of introducing an internal amplification control to reference samples, in the form of a nullomer barcode which is based upon sequences absent or rare from publically accessible DNA databases. The detection of this barcode would indicate that the source of analyzed DNA was from a reference sample provided by an individual, and not from an evidence sample. We demonstrate that the nullomers can be added directly to collection devices (FTA paper) to allow tagging during the process of sample collection. We show that such nullomer oligonucleotides can be added to existing forensic typing and quantification kits, without affecting genotyping or quantification results. Finally, we show that even when diluted a million-fold and spilled on a knife, the nullomer tags can be clearly detected. These tags support the National Research Council of the National Academy recommendation that "Quality control procedures should be designed to identify mistakes, fraud, and bias" in forensic science (National Academy of Sciences, 2009).