T-Cell Engagers Based Bioassay for Evaluation of PD-1/PD-L1 Inhibitors Activity.

PD-1/PD-L1-based therapy has been named a revolution in cancer treatment. By the end of 2018, more than 100 anti-PD-1 and anti-PD-L1 antibodies were in various stages of development, and more than 2000 clinical trials with their use have been registered. Characterization of such antibodies requires a bioassay to determine their biological activity. In this study, we developed a cell-based bioassay for analyzing the activity of anti-PD-1 and anti-PD-L1 antibodies. We chose reporter system consisting of two cell lines and compared several approaches for activation of effector cell line based on superantigens, soluble anti-CD3 antibodies, transmembrane anti-CD3 antibodies, chimeric antigenic receptors (CARs) and bispecific T-cell engager antibodies. The bispecific T-cell engager antibodies offer several advantages over the other approaches. We characterized the bioassay and demonstrated its applicability for analyzing the activity of anti-PD-1 and anti-PD-L1 antibodies. The proposed bioassay can be useful in the development of new therapeutic agents and methods for their characterization.

Thiol antioxidants in combination with vitamin B12 induce apoptotic death of human lymphocytic leukemia cells by destabilization of lysosomes with the involvement of iron ions.

The extensively used thiol antioxidants (dithiothreitol, glutathione, and N-acetylcysteine) in combination with hydroxycobalamine (vitamin B12) gain toxic activity in relation to human lymphocytic leukemia cell line HL60. Combined treatment with thiol and vitamin B12 was followed by early destabilization of lysosomes and apoptotic death of cells. The cytotoxic effect was abolished by caspase inhibitors. An iron-chelating agent deferoxamine partly prevented cell death, while lysosomal protease inhibitor pepstatin produced no protective effect.

Hydroxycobalamin catalyzes the oxidation of diethyldithiocarbamate and increases its cytotoxicity independently of copper ions.

It is known that some metals (Cu, Zn, Cd, Au) markedly increase the toxic effect of thiocarbamates. It was shown in the present study that hydroxycobalamin (a form of vitamin B12, HOCbl), which incorporates cobalt, significantly enhances the cytotoxicity of diethyldithiocarbamate (DDC), decreasing its IC50 value in tumor cells three to five times. The addition of HOCbl to aqueous DDC solutions accelerated the reduction of oxygen. No hydrogen peroxide accumulation was observed in DDC + HOCbl solutions; however, catalase slowed down the oxygen reduction rate. Catalase as well as the antioxidants N-acetylcysteine (NAC) and glutathione (GSH) partially inhibited the cytotoxic effect of DDC + HOCbl, whereas ascorbate, pyruvate, and tiron, a scavenger of superoxide anion, had no cytoprotective effect. The administration of HOCbl into DDC solutions (> 1 mM) resulted in the formation of a crystalline precipitate, which was inhibited in the presence of GSH. The data of UV and NMR spectroscopy and HPLC and Mass Spectrometry (LC/MS) indicated that the main products of the reaction of DDC with HOCbl are disulfiram (DSF) and its oxidized forms, sulfones and sulfoxides. The increase in the cytotoxicity of DDC combined with HOCbl occurred both in the presence of Cu2+ in culture medium and in nominally Cu-free solutions, as well as in growth medium containing the copper chelator bathocuproine disulfonate (BCS). The results indicate that HOCbl accelerates the oxidation of DDC with the formation of DSF and its oxidized forms. Presumably, the main cause of the synergistic increase in the toxic effect of DDC + HOCbl is the formation of sulfones and sulfoxides of DSF.

Author Correction: Long-range non-diffusive spin transfer in a Hall insulator.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper.

Long-range non-diffusive spin transfer in a Hall insulator.

We report on optical visualization of spin propagation more than 100 µm. We present an electronic system in a new state of aggregation, the magnetofermionic condensate, in which the lowest-energy spin excitations - photoexcited spin-triplet magnetoexcitons - freely propagate over long distances, in the order of a millimeter, which implies non-diffusion spin transport. Our results open up a completely new system suitable for spintronic devices.

Plant promoter prediction with confidence estimation.

Accurate prediction of promoters is fundamental to understanding gene expression patterns, where confidence estimation is one of the main requirements. Using recently developed transductive confidence machine (TCM) techniques, we developed a new program TSSP-TCM for the prediction of plant promoters that also provides confidence of the prediction. The program was trained on 132 and 104 sequences and tested on 40 and 25 sequences (containing TATA and TATA-less promoters, respectively) with known transcription start sites (TSSs). As negative training samples for TCM learning we used coding and intron sequences of plant genes annotated in the GenBank. In the test set of TATA promoters, the program correctly predicted TSS for 35 out of 40 (87.5%) genes with a median deviation of several base pairs from the true site location. For 25 TATA-less promoters, TSSs were predicted for 21 out of 25 (84%) genes, including 14 cases of 5 bp distance between annotated and predicted TSSs. Using TSSP-TCM program we annotated promoters in the whole Arabidopsis genome. The predicted promoters were in good agreement with the start position of known Arabidopsis mRNAs. Thus, TCM technique has produced a plant-oriented promoter prediction tool of high accuracy. TSSP-TCM program and annotated promoters are available at http://mendel.cs.rhul.ac.uk/mendel.php?topic=fgen.

PromH: Promoters identification using orthologous genomic sequences.

Accurate prediction of promoters is fundamental for understanding gene expression patterns, cell specificity and development. In the studies of conserved features of regulatory regions of orthologous genes, it was observed that major promoter functional components such as transcription start points, TATA-boxes and regulatory motifs, are significantly more conservative than the sequences around them (70-100% compared with 30-50%). To improve promoter identification accuracy, we employed these findings in a new program, PromH, created by extending the TSSW program feature set. PromH uses linear discriminant functions that take into account conservation features and nucleotide sequences of promoter regions in pairs of orthologous genes. The program was tested on two sets of pairs of orthologous, mostly human and rodent, sequences with known transcription start sites (TSS), annotated to have TATA (21 genes, 11 orthologous pairs) and TATA-less (38 genes, 19 pairs) promoters, respectively. The program correctly predicted TSS for all 21 genes of the first set with a median deviation of 2 bp from true site location. Only for two genes, was there significant (46 and 105 bp) discrepancy between predicted and annotated TSS positions. For 38 TATA-less promoters from the second set, TSS was predicted for 27 genes, in 14 cases within 10 bp distance from annotated TSS, and in 21 cases--within 100 bp distance. Despite more discrepancies between predicted and annotated TSS for genes from the second set, these results are consistent with observations of much higher occurrence of multiple TSS in TATA-less promoters. In any case, our results show that PromH identifies TSS positions significantly more accurately than any other published promoter prediction method. The PromH program is available at http://www.softberry.com/berry.phtml?topic=promh.

SpliceDB: database of canonical and non-canonical mammalian splice sites.

A database (SpliceDB) of known mammalian splice site sequences has been developed. We extracted 43 337 splice pairs from mammalian divisions of the gene-centered Infogene database, including sites from incomplete or alternatively spliced genes. Known EST sequences supported 22 815 of them. After discarding sequences with putative errors and ambiguous location of splice junctions the verified dataset includes 22 489 entries. Of these, 98.71% contain canonical GT-AG junctions (22 199 entries) and 0.56% have non-canonical GC-AG splice site pairs. The remainder (0.73%) occurs in a lot of small groups (with a maximum size of 0.05%). We especially studied non-canonical splice sites, which comprise 3.73% of GenBank annotated splice pairs. EST alignments allowed us to verify only the exonic part of splice sites. To check the conservative dinucleotides we compared sequences of human non-canonical splice sites with sequences from the high throughput genome sequencing project (HTG). Out of 171 human non-canonical and EST-supported splice pairs, 156 (91.23%) had a clear match in the human HTG. They can be classified after sequence analysis as: 79 GC-AG pairs (of which one was an error that corrected to GC-AG), 61 errors corrected to GT-AG canonical pairs, six AT-AC pairs (of which two were errors corrected to AT-AC), one case was produced from a non-existent intron, seven cases were found in HTG that were deposited to GenBank and finally there were only two other cases left of supported non-canonical splice pairs. The information about verified splice site sequences for canonical and non-canonical sites is presented in SpliceDB with the supporting evidence. We also built weight matrices for the major splice groups, which can be incorporated into gene prediction programs. SpliceDB is available at the computational genomic Web server of the Sanger Centre: http://genomic.sanger.ac. uk/spldb/SpliceDB.html and at http://www.softberry. com/spldb/SpliceDB.html.

Analysis of canonical and non-canonical splice sites in mammalian genomes.

A set of 43 337 splice junction pairs was extracted from mammalian GenBank annotated genes. Expressed sequence tag (EST) sequences support 22 489 of them. Of these, 98.71% contain canonical dinucleotides GT and AG for donor and acceptor sites, respectively; 0.56% hold non-canonical GC-AG splice site pairs; and the remaining 0.73% occurs in a lot of small groups (with a maximum size of 0.05%). Studying these groups we observe that many of them contain splicing dinucleotides shifted from the annotated splice junction by one position. After close examination of such cases we present a new classification consisting of only eight observed types of splice site pairs (out of 256 a priori possible combinations). EST alignments allow us to verify the exonic part of the splice sites, but many non-canonical cases may be due to intron sequencing errors. This idea is given substantial support when we compare the sequences of human genes having non-canonical splice sites deposited in GenBank by high throughput genome sequencing projects (HTG). A high proportion (156 out of 171) of the human non-canonical and EST-supported splice site sequences had a clear match in the human HTG. They can be classified after corrections as: 79 GC-AG pairs (of which one was an error that corrected to GC-AG), 61 errors that were corrected to GT-AG canonical pairs, six AT-AC pairs (of which two were errors that corrected to AT-AC), one case was produced from non-existent intron, seven cases were found in HTG that were deposited to GenBank and finally there were only two cases left of supported non-canonical splice sites. If we assume that approximately the same situation is true for the whole set of annotated mammalian non-canonical splice sites, then the 99.24% of splice site pairs should be GT-AG, 0.69% GC-AG, 0.05% AT-AC and finally only 0.02% could consist of other types of non-canonical splice sites. We analyze several characteristics of EST-verified splice sites and build weight matrices for the major groups, which can be incorporated into gene prediction programs. We also present a set of EST-verified canonical splice sites larger by two orders of magnitude than the current one (22 199 entries versus approximately 600) and finally, a set of 290 EST-supported non-canonical splice sites. Both sets should be significant for future investigations of the splicing mechanism.

Laser-synthesized oxide-passivated bright Si quantum dots for bioimaging.

Crystalline silicon (Si) nanoparticles present an extremely promising object for bioimaging based on photoluminescence (PL) in the visible and near-infrared spectral regions, but their efficient PL emission in aqueous suspension is typically observed after wet chemistry procedures leading to residual toxicity issues. Here, we introduce ultrapure laser-synthesized Si-based quantum dots (QDs), which are water-dispersible and exhibit bright exciton PL in the window of relative tissue transparency near 800 nm. Based on the laser ablation of crystalline Si targets in gaseous helium, followed by ultrasound-assisted dispersion of the deposited films in physiological saline, the proposed method avoids any toxic by-products during the synthesis. We demonstrate efficient contrast of the Si QDs in living cells by following the exciton PL. We also show that the prepared QDs do not provoke any cytoxicity effects while penetrating into the cells and efficiently accumulating near the cell membrane and in the cytoplasm. Combined with the possibility of enabling parallel therapeutic channels, ultrapure laser-synthesized Si nanostructures present unique object for cancer theranostic applications.

New elements of glucocorticoid-receptor binding sites of hormone-regulated genes.

The structure of the DNA regions recognized by glucocorticoid-receptor complexes (GIRC) was analyzed using frequency matrices and a modified perceptron method. Some complementary conservative elements which may modulate the efficiency of GIRC binding were found at both sides of the previously established conserved nucleotide sequence (core) (Beato, M. et al. (1987) J. Steroid Biochem. 27, 9-14). A criterion based on the concurrent use of several perceptron matrices to search for the potential GIRC binding site sequences has been worked out. By applying this criterion 73 sites were identified in 28 sequences of glucocorticoid regulated genes and 7 sites were identified in 26 sequences independent from glucocorticoid regulation.

Protein secondary structure prediction using local alignments.

The accuracy of secondary structure prediction methods has been improved significantly by the use of aligned protein sequences. The PHD method and the NNSSP method reach 71 to 72% of sustained overall three-state accuracy when multiple sequence alignments are with neural networks and nearest-neighbor algorithms, respectively. We introduce a variant of the nearest-neighbor approach that can achieve similar accuracy using a single sequence as the query input. We compute the 50 best non-intersecting local alignments of the query sequence with each sequence from a set of proteins with known 3D structures. Each position of the query sequence is aligned with the database amino acids in alpha-helical, beta-strand or coil states. The prediction type of secondary structure is selected as the type of aligned position with the maximal total score. On the dataset of 124 non-membrane non-homologous proteins, used earlier as a benchmark for secondary structure predictions, our method reaches an overall three-state accuracy of 71.2%. The performance accuracy is verified by an additional test on 461 non-homologous proteins giving an accuracy of 71.0%. The main strength of the method is the high level of prediction accuracy for proteins without any known homolog. Using multiple sequence alignments as input the method has a prediction accuracy of 73.5%. Prediction of secondary structure by the SSPAL method is available via Baylor College of Medicine World Wide Web server.

Prediction of protein secondary structure by combining nearest-neighbor algorithms and multiple sequence alignments.

Recently Yi & Lander used a neural network and nearest-neighbor method with a scoring system that combined a sequence-similarity matrix with the local structural environment scoring scheme described by Bowie and co-workers for predicting protein secondary structure. We have improved their scoring system by taking into consideration N and C-terminal positions of alpha-helices and beta-strands and also beta-turns as distinctive types of secondary structure. Another improvement, which also decreases the time of computation, is performed by restricting a data base with a smaller subset of proteins that are similar with a query sequence. Using multiple sequence alignments rather than single sequences and a simple jury decision procedure our method reaches a sustained overall three-state accuracy of 72.2%, which is better than that observed for the most accurate multilayered neural-network approach, tested on the same data set of 126 non-homologous protein chains.

Light-hole quantization in the optical response of ultra-wide GaAs/Al(x)Ga(1-x)As quantum wells.

Temperature-dependent reflectivity and photoluminescence spectra are studied for undoped ultra-wide 150 and 250 nm GaAs quantum wells. It is shown that spectral features previously attributed to a size quantization of the exciton motion in the z-direction coincide well with energies of quantized levels for light holes. Furthermore, optical spectra reveal very similar properties at temperatures above the exciton dissociation point.

Predicting alpha-helix and beta-strand segments of globular proteins.

All current methods of protein secondary structure prediction are based on evaluation of a single residue state. Although the accuracy of the best of them is approximately 60-70%, for reliable prediction of tertiary structure it is more useful to predict an approximate location of alpha-helix and beta-strand segments, especially prolonged ones. We have developed a simple method for protein secondary structure prediction which is oriented on the location of secondary structure segments. The method uses linear discriminant analysis to assign segments of a given amino acid sequence a particular type of secondary structure, by taking into account the amino acid composition of internal parts of segments as well as their terminal and adjacent regions. Four linear discriminant functions were constructed for recognition of short and long alpha-helix and beta-strand segments respectively. These functions combine three characteristics: hydrophobic moment, segment singlet, and pair preferences to an alpha-helix or beta-strand. The last two characteristics are calculated by summing the preference parameters of single residues and pairs of residues located in a segment and its adjacent regions. The final program SSP predicts all possible potential alpha-helices and beta-strands and resolves some possible overlap between them. Overall three-state (alpha, beta, c) prediction gives approximately 65.1% correctly predicted residues on 126 non-homologous proteins using the jackknife test procedure. Analysis of the prediction results shows a high prediction accuracy of long secondary structure segments (approximately 89% of alpha-helices of length > 8 and approximately 71% of beta-strands of length > 6 are correctly located with probability of correct prediction 0.82 and 0.78 respectively.(ABSTRACT TRUNCATED AT 250 WORDS)

Assignment of position-specific error probability to primary DNA sequence data.

DNA sequence predicted from polyacrylamide gel-based technologies is inaccurate because of variations in the quality of the primary data due to limitations of the technology, and to sequence-specific variations due to nucleotide interactions within the DNA molecule and with the gel. The ability to recognize the probability of error in the primary data will be useful in reconstructing the target sequence of a DNA sequencing project, and in estimating the accuracy of the final sequence. This paper describes the use of linear discriminant analysis to assign position-specific probabilities of incorrect, over- and under-prediction of nucleotides for each predicted nucleotide position in primary sequence data generated by a gel-based DNA sequencing technology. Using this method, most of the error potential in primary sequence data can be assigned to a limited number of discrete positions. The use of probability values in the sequence reconstruction process, and in estimating the accuracy of consensus sequence determination is described.

Identification of human gene functional regions based on oligonucleotide composition.

Accurate recognition of coding and intron regions within large regions of uncharacterized genomic DNA is an unsolved problem. A data base of more than 4,240,791 bp coding and 7,790,682 bp noncoding human sequences was extracted from GenBank to develop a function for locating coding regions in anonymous sequences. Several coding measures based on oligonucleotide preferences were tested on a control set that including 1/3 of all extracted sequences. An accuracy of separation of coding/noncoding regions is 87% for 9 bp oligonucleotides on 54 bp windows and 91% on 108 bp windows, respectively. For separation of coding/intron regions the accuracy is 89-90% for 8 bp oligonucleotides on 54 bp windows and up to 95% on 108 bp windows. Using the information about preferences of octanucleotides in protein coding and intron regions and significant triplet frequencies as a function of position near splice junctions, a joint splice site prediction scheme was developed. The accuracy of the joint scheme for predicting splice site positions on the test set was about 96-97%, which exceeds the accuracy of the previously reported splice site selection method based on a more complex artificial neural network approach. A model of splicing using poly-G(C) rich exon flanking sequences is suggested. A remarkable difference of oligonucleotide composition 5'- and 3'- gene regions is displayed and applied in a gene structure predictive system.

Recognition of 3'-processing sites of human mRNA precursors.

We have developed a computer program POLYAH and an algorithm for the identification of 3'-processing sites of human mRNA precursors. The algorithm is based on a linear discriminant function (LDF) trained to discriminate real poly(A) signal regions from the other regions of human genes possessing the AATAAA sequence which is most likely non-functional. As the parameters of LDF, various significant contextual characteristics of sequences surrounding AATAAA signals were used. An accuracy of method has been estimated on a set of 131 poly(A) regions and 1466 regions of human genes having the AATAAA sequence. When the threshold was set to predict 86% of poly(A) regions correctly, specificity of 51% and correlation coefficient of 0.62 had been achieved. The precision of this approach is better than for the other methods and has been tested on a larger data set. POLYAH can be used through World Wide Web (at Gene-Finder Home page: URL http:@dot.imgen.bcm.tmc.edu:9331/gene-finder/ gf.html) or by sending files with uncharacterized human sequences to the University of Houston or Weizmann Institute of Science e-mail servers.

Ab initio gene finding in Drosophila genomic DNA.

Ab initio gene identification in the genomic sequence of Drosophila melanogaster was obtained using (human gene predictor) and Fgenesh programs that have organism-specific parameters for human, Drosophila, plants, yeast, and nematode. We did not use information about cDNA/EST in most predictions to model a real situation for finding new genes because information about complete cDNA is often absent or based on very small partial fragments. We investigated the accuracy of gene prediction on different levels and designed several schemes to predict an unambiguous set of genes (annotation CGG1), a set of reliable exons (annotation CGG2), and the most complete set of exons (annotation CGG3). For 49 genes, protein products of which have clear homologs in protein databases, predictions were recomputed by Fgenesh+ program. The first annotation serves as the optimal computational description of new sequence to be presented in a database. Reliable exons from the second annotation serve as good candidates for selecting the PCR primers for experimental work for gene structure verification. Our results shows that we can identify approximately 90% of coding nucleotides with 20% false positives. At the exon level we accurately predicted 65% of exons and 89% including overlapping exons with 49% false positives. Optimizing accuracy of prediction, we designed a gene identification scheme using Fgenesh, which provided sensitivity (Sn) = 98% and specificity (Sp) = 86% at the base level, Sn = 81% (97% including overlapping exons) and Sp = 58% at the exon level and Sn = 72% and Sp = 39% at the gene level (estimating sensitivity on std1 set and specificity on std3 set). In general, these results showed that computational gene prediction can be a reliable tool for annotating new genomic sequences, giving accurate information on 90% of coding sequences with 14% false positives. However, exact gene prediction (especially at the gene level) needs additional improvement using gene prediction algorithms. The program was also tested for predicting genes of human Chromosome 22 (the last variant of Fgenesh can analyze the whole chromosome sequence). This analysis has demonstrated that the 88% of manually annotated exons in Chromosome 22 were among the ab initio predicted exons. The suite of gene identification programs is available through the WWW server of Computational Genomics Group at http://genomic.sanger.ac.uk/gf. html.