imagine (Institute of molecular genetics and genetic engineering)
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Antitumor activity of natural pigment violacein against osteosarcoma and rhabdomyosarcoma cell lines
No full textSarcomas are rare and heterogenic tumors with unclear etiology. They develop in bone and connective tissue, mainly in pediatric patients. To increase efficacy of current therapeutic options, natural products showing selective toxicity to tumor cells are extensively investigated. Here, we evaluated antitumor activity of bacterial pigment violacein in osteosarcoma (OS) and rhabdomyosarcoma (RMS) cell lines.This is the peer-reviewed version of the article: Milošević, E., Stanisavljević, N., Bošković, S., Stamenković, N., Novković, M., Bavelloni, A., Cenni, V., Kojić, S.,& Jasnić, J.. (2023). Antitumor activity of natural pigment violacein against osteosarcoma and rhabdomyosarcoma cell lines. in Journal of Cancer Research and Clinical Oncology. [https://doi.org/10.1007/s00432-023-04930-9]Supp. material: [https://imagine.imgge.bg.ac.rs/handle/123456789/1929
Supplementary data for the article: Milošević, E., Stanisavljević, N., Bošković, S., Stamenković, N., Novković, M., Bavelloni, A., Cenni, V., Kojić, S.,& Jasnić, J.. (2023). Antitumor activity of natural pigment violacein against osteosarcoma and rhabdomyosarcoma cell lines. in Journal of Cancer Research and Clinical Oncology. https://doi.org/10.1007/s00432-023-04930-9
Get PDFSupplementary material for: Milošević, E., Stanisavljević, N., Bošković, S., Stamenković, N., Novković, M., Bavelloni, A., Cenni, V., Kojić, S.,& Jasnić, J.. (2023). Antitumor activity of natural pigment violacein against osteosarcoma and rhabdomyosarcoma cell lines. in Journal of Cancer Research and Clinical Oncology. [https://doi.org/10.1007/s00432-023-04930-9]Related to published version: [https://imagine.imgge.bg.ac.rs/handle/123456789/1918]Related to accepted verison: [https://imagine.imgge.bg.ac.rs/handle/123456789/1928
A tale of two stories: data-driven precision medicine and precision public health
Get PDFBig Data offers opportunities in health care to refine individuals’ characterization and
thus complement traditional precision medicine approaches toward individual-targeted
prevention, diagnosis and treatment management. Not surprisingly, network theory plays
a vital role in modelling Big Data: the higher the number of measurements, the higher the
number of potential relationships or dependencies among them. Recent developments
have shown the complementary value of personalizing population-based networks
for individuals (Menche et al. 2017, Dimitrakopoulos et al. 2018) or deriving individualspecific
networks via populations of cells (Gosak et al. 2018, Li et al. 2023).
Individual-specific networks do not necessarily require repeated measurements over time
or in space. Reverse-engineered individual-specific networks (Kuijjer et al. 2019) from an
aggregate network (hereafter referred to as ISNs) allow for investigating the impact of
individual-level network wirings, paths or connectivity on medical decision-making in the
individual’s interest. Wondering about the utility of these ISNs, we illustrate by example
from microbiome and gene co-expression experiments how ISNs give complementary
insights in dynamic network biomarker identification and can reveal (genetic modifiers of)
co-eQTLs as direct or indirect regulators of gene co-expression.Book of abstract: 4th Belgrade Bioinformatics Conference, June 19-23, 202
Pangenomic Alignment: Strings plus Graphs
Get PDFThe use of only one or a few reference genomes for DNA alignment is known to bias
research results and medical diagnoses, but aligning against many reference genomes
has been problematic. If we represent such a pangenomic reference as a set of strings,
then each seed we find in a DNA read may occur in many of the genomes, so even
reporting all those occurrences can be slow, and extending and chaining seeds can be
infeasible. On the other hand, if we represent them as a graph then --- even apart from
the significant technical challenges of indexing graphs --- we may find many chimeric
matches. The more of humanity’s genetic diversity we try to represent in the graph, the
fuzzier it becomes, and the greater the probability of spurious results.
Most research on pangenomic alignment uses either a string representation or a graph
representation, but not both. In this talk we first describe how a tool called MONI indexes
a pangenomic reference as a set of strings in small space such that later, for each maximal
exact match in a given read, we can quickly find that match’s length, the position of one of
its occurrences in the set of strings, and the lexicographic rank of the suffix starting with
that occurrence. We then describe how a tool called MARIA will, when fully implemented,
store a pangenomic reference as a graph in small space such that, given MONI’s output
about a maximal exact match, we can quickly report all the non-chimeric occurrences of
that match in the graph.
Combining MONI and MARIA will give us the advantages of working with both strings and
graphs: we index the set of reference genomes, the whole set of reference genomes, and
nothing but the set of reference genomes, but for each maximal exact match we output
relatively few occurrences in the graph, which are easy to use later in a pipeline.Book of abstract: 4th Belgrade Bioinformatics Conference, June 19-23, 202
Application of classification algorithms for hip implant surface topographies
Get PDFExperimental studies have shown that lower shear stress values lead to better femoral
bone – hip implant connection. Numerical simulations have provided option to reduce
the number of experimental studies through analysis of different hip implant surface
topographies. However, this approach takes time as there are different model parameters
that should be considered in order to understand how they affect the obtained shear
stress values. The use of classification algorithms is an approach that could reduce the
time required for simulation by providing information about models with biggest potential.
Eleven model parameters related to model and surface topography were considered
in combination with four classification algorithms - Support Vector Machines (SVM), K
- Nearest Neighbor (KNN), Decision Tree (DT), and Random Forest (RF). The considered
parameters were: Number of half-cylinders lengthwise (>0); Number of half-cylinder rows
(≥0); Half cylinders added or removed from the surface (0 – removed; 1 - added); Distance
between half-cylinders lengthwise (≥0); Distance between half-cylinders widthwise
(≥0); Number of different radius values (1 or 2); Radius 1 value (>0); Radius 2 value (≥0);
Distance from the edge where loading is located (≥0); Distance from the other edge of the
model (≥0); Model includes trabecular bone (0 – not included; 1 - included). The aim was
to apply previously mentioned algorithms to obtain information if the maximum shear
stress value was above or below user-defined threshold. The obtained results show that
this approach can be useful to obtain preliminary information about models that should
be numerically analyzed.Book of abstract: 4th Belgrade Bioinformatics Conference, June 19-23, 202
Decoding Cystic Fibrosis Phenotype
Get PDFCystic fibrosis (CF) is a monogenic autosomal recessive disease caused by mutations in
transmembrane conductance regulator (CFTR) gene. The golden standard for the diagnosis
of CF is sweat chloride testing (>60 mmol/L) together with the identification of two CFcausing
variants of CFTR gene. Nevertheless, about 0.01% of patients with elevated sweat
chloride and high clinical suspicion of CF do not carry any CF-causing variants.
Here we present analysis of whole exome sequencing (WES) results for two patients with
elevated sweat chloride levels and clinical presentation of CF in whom no CF-causing
mutations were detected after CFTR gene whole coding region sequencing, and large
insertion/deletion testing.
Genomic DNA was extracted from whole blood, subjected to library preparation using
DNA nanoball technology from BGI and sequenced on DNBSEQ-G400 (MGI). Produced
fastq files were mapped to hg38 reference genome using BWA/SAM tools. VCF files were
generated using GATK (BaseRecalibrator, HaplotypeCaller) and annotated with InterVar
and AnnoVar tools. Filtering of detected variants for disease relevance was done using
the following criteria: QC Filter, GnomAD Allele Frequency, Functional consequences and
phenotype-genotype relationship.
In both patients, similar number of variants predicted to impair protein function were
detected (27 and 25). In two genes (CACNA1H and MUC5B) missense type variants
were found in both patients and loss of function variants were found in 7 and 11 genes,
respectively. Functional assessment of selected variants is underway.
Bioinformatics analyses are a valuable tool enabling identification of underlining genetic
bases of disease phenotype, important in the context of optimal patient management and
targeted therapies.Book of abstract: 4th Belgrade Bioinformatics Conference, June 19-23, 202
Single cell 3’ transcriptome profiling
Get PDFWhole 3’ transcriptome profiling at the single cell level opens up new abilities for researchers to
answer complex questions. Thousands of individual cells per sample are Barcoded separately to
index the transcriptome of each cell individually. It is done by partitioning thousands of cells into
nanoliter-scale Gel Beads-in-emulsion (GEMs), where cells are delivered at a limiting dilution, such
that the majority (~90-99%) of generated GEMs contain no cell. The 16 bp 10x Barcode and 12 bp
UMI are encoded in Read 1, while the poly(dT) primers are used in this protocol for generating Single
Cell 3’ Gene Expression libraries. After GEM generation, copartitioned cells are lysed and reverse
transcription (RT) was performed after which all cDNA from single cell share a common Barcode.
Full-length cDNA was amplified via PCR to generate sufficient mass for library construction. This is
followed by enzymatic fragmentation and size selection to optimize the cDNA amplicon size. Library
construction was finished via End Repair, A-tailing, Adaptor Ligation, and PCR. P5, P7, i7 and i5
sample index, and TruSeq Read 2 (read 2 primer sequence) were added. TruSeq Read 1 and TruSeq
Read 2 are standard Illumina sequencing primer sites used in paired-end sequencing. The library
prepared in this way, containing the P5 and P7 primers, is ready for Illumina amplification.Book of abstract: 4th Belgrade Bioinformatics Conference, June 19-23, 202
Enzymatic functionalization of liquid phase exfoliated graphene using horseradish peroxidase and laccase
No full textWe present a novel approach for the enzymatic functionalization of graphene, utilizing horseradish peroxidase (HPO) and laccase (LC) from Trametes versicolor. This study demonstrates, for the first time, the covalent modification of non-homogeneous graphene with a low surface-to-volume ratio, both in solution and on solid support. Through thermogravimetry analysis, we estimate the degree of functionalization to be 11% with HPO and 4% with LC, attributed to the varying redox potentials of the enzymes. This work highlights the potential of enzymatic reactions for tailored functionalization of graphene under mild conditions.This work was supported by PMI/Centre for Leadership Belgrade
through the "Start-up for Science" program. We would also like to
acknowledge the Alexander von Humboldt Foundation for granting A.
M. a renewed stay in Germany. We are grateful to Professor Andreas
Hirsch for providing access to the Raman spectrometer and TGA/M
Genome-wide association analysis for severe COVID-19 in Serbian population
Get PDFHost genetics, an important contributor to the COVID-19 clinical susceptibility and severity,
currently is the focus of multiple genome-wide association studies (GWAS) in populations
affected by the pandemic. This is the first study from Serbia that performed a GWAS of
COVID-19 outcomes to identify genetic risk markers of disease severity. A group of 128
hospitalized COVID-19 patients from the Serbian population was enrolled in the study.
We conducted a GWAS comparing (1) patients with pneumonia (n = 80) against patients
without pneumonia (n = 48), and (2) severe (n = 34) against mild disease (n = 48) patients,
using a genotyping array followed by imputation of missing genotypes. We have detected
a significant signal associated with COVID-19 related pneumonia at locus 13q21.33, with
a peak residing upstream of the gene KLHL1 (p = 1.91 × 10−8). Our study also replicated
a previously reported COVID-19 risk locus at 3p21.31, identifying lead variants in SACM1L
and LZTFL1 genes suggestively associated with pneumonia (p = 7.54 × 10−6) and
severe COVID-19 (p = 6.88 × 10−7), respectively. Suggestive association with COVID-19
pneumonia has also been observed at chromosomes 5p15.33 (IRX, NDUFS6,MRPL36, p
= 2.81 × 10−6), 5q11.2 (ESM1, p = 6.59 × 10−6), and 9p23 (TYRP1,LURAP1L, p = 8.69 ×
10−6). The genes located in or near the risk loci are expressed in neural or lung tissues, and
have been previously associated with respiratory diseases such as asthma and COVID-19
or reported as differentially expressed in COVID-19 gene expression profiling studies.
Our results revealed novel risk loci for pneumonia and severe COVID-19 disease which
could contribute to a better understanding of the COVID-19 host genetics in different
populations.Book of abstract: 4th Belgrade Bioinformatics Conference, June 19-23, 202
Application of principal component analysis (PCA) and analytical hierarchy process (AHP) in analysis of articulatory characteristics of phonemes of children with 22q11.2 Deletion Syndrome
Get PDF22q11.2 deletion syndrome (22q11.2DS is caused by 22q11.2 microdeletion, one of
the strongest known risk factors for development of neurodevelopmental disorders.
About 70% patients with 22q11.2DS have speech and language impairments. In the
literature, there is no data about articulatory characteristics of phonemes of children
with 22q11.2DS, monolingual native speakers of South Slavic languages. Here we, by
applying Global Articulation Test, analyzed articulatory characteristics of phonemes of
children with 22q11.2DS, monolingual native speakers of the Serbian language (group
E1), children with a phenotype resembling 22q11.2DS but without the microdeletion
(group E2), children with non-syndromic congenital heart malformations (since children
with these malformations may exhibit a speech and language impairments) (group
E3) and their peers with typical speech-sound development (group C). Results of PCA
indicated that the groups can be distinguished based on the pronunciation of phonemes,
and that the pronunciation of the phonemes “Č ⟨tʃ⟩”, “Dž ⟨ʤ⟩”, “Š ⟨∫⟩”, “Ž ⟨ʒ⟩”, “R”, and “Lj ⟨ʎ⟩”
contributes the most to the variability between the groups. Results of AHP revealed that
the pronunciation of the phonemes “Č ⟨tʃ⟩”, “Dž ⟨ʤ⟩”, “Š ⟨∫⟩”, “Ž ⟨ʒ⟩”, “R”, and “Lj ⟨ʎ⟩” was
rated the worst in the group E1. In conclusion, obtained results indicate that the presence
of 22q11.2 microdeletion influences articulation skills of carriers.Book of abstract: 4th Belgrade Bioinformatics Conference, June 19-23, 202