Comparison of antimicrobial effect of selenium nanoparticles and silver nanoparticles coated orthodontic mini-implants – An in vitro study

Objectives:

Mini-implants have earned a significant role in orthodontic treatment, by augmenting anchorage requirements. Peri-implantitis contributes to miniscrew failures where progressive peri-implant bone loss occurs in conjunction with soft-tissue inflammation due to the growth of microorganisms such as Streptococcus and Lactobacillus. Nanoparticles have increased surface area and have increased interactions with biological targets like bacteria. This study aims to investigate the antimicrobial activity of silver nanoparticles (AgNP) and selenium nanoparticles (SeNPs) on orthodontic mini-implants.

Material and Methods:

Mini-implant (Ti-6Al-4V) was coated with AgNP and SeNP with biopolymer (Ti-BPAgNP and Ti-BPSeNP) by dip-coating technique. The crystal structure and crystallite size of AgNPs and SeNPs were characterized by the X-ray diffraction (XRD) method. The size distribution and morphology of SeNP and AgNP were determined by a scanning electron microscope (SEM). The antibacterial activity of Ti-BP-AgNP and Ti-BPSeNP was detected from the zone of inhibition by disk diffusion assay.

Results:

The SEM image of AgNP was roughly spherical, uniformly distributed and SeNPs were spherical, well distributed on the biopolymer surface. The area of the zone of inhibition of Ti-BP-SeNP-coated mini-implants shows a negligible difference in antibacterial activity compared to Ti-BPAgNP-coated mini-implants.

Conclusion:

Ti-BP-AgNP and Ti-BP-SeNP showed that a strong antibacterial activity was against Lactobacillus and Staphylococcus aureus. Antibacterial activity against Streptococcus mutans was slightly less than observed in other bacteria. SeNP shows only a marginal difference in antibacterial activity when compared to AgNP.

Abstract PL1: Breast Tumor Evolution and Intratumor Heterogeneity - Insights from Single Cell Genomics

Breast tumors evolve from single cells in the ducts and acquire mutations leading to divergent lineages and intratumor heterogeneity in invasive cancers. To understand the genomic evolution of breast cancers during complex evolutionary processes including initiation, invasion and therapeutic resistance we have developed single cell sequencing (SCS) methods. I will discuss our efforts in applying SCS methods to study invasion in 10 premalignant breast cancer patients with ductal-carcinoma-in-situ (DCIS), which led to a discovery of early punctuated copy number evolution in the ducts and multi-clonal invasion. I will also discuss our work in applying both single cell DNA and RNA sequencing methods to study chemoresistance evolution in 20 triple-negative breast cancer patients using longitudinal samples, which identified an adaptive genomic evolution and acquired transcriptional reprogramming during resistance. Finally I will present unpublished work on our efforts to develop a 'Human Breast Cell Atlas' of cell types and cell states (transcriptional programs) of normal cell types, and recent work on delineating copy number evolution in BRCA-positive breast cancer patients.

Citation Format: Navin N. Breast Tumor Evolution and Intratumor Heterogeneity - Insights from Single Cell Genomics [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr PL1.

Abstract GS1-02: Towards a human breast cell atlas

The human breast tissue consists of lobules connected to a complex network of ducts that are evolutionarily designed to produce and transport milk to nourish offspring. Histopathology has identified 10 major cell types based on morphological features but have provided limited information on cell states - the transcriptional programs of cell types that reflect different biological functions. In this study, we have generated an unbiased 'cell atlas' of the normal human breast to define the cell types and cell states using single cell RNA sequencing methods. We performed 3' microdroplet based single cell RNA sequencing of 31,442 stromal cells from 11 women with pathologically normal breast tissues that were collected from mastectomies. Unbiased expression analysis identified three major cell types: epithelial cells (luminal and basal), fibroblasts and endothelial cells, in addition to several minor cell types: macrophages, T-cells, natural killer cells, pericytes and smooth muscle cells. Analysis of cell states of these cell types revealed different transcriptional programs in luminal epithelial cells (hormone receptor positive and secretory), basal epithelial cells (myoepithelial or basement-like), endothelial cells (lymphatic or vascular), macrophages (M1 or M2) and fibroblasts (three subgroups) and provided insight into progenitors of each cell types. These data provide a valuable reference for the research community and will provide new insights into how normal cell types are transformed in the tumor microenvironment to promote or inhibit the progression of breast cancer.

Citation Format: Seth TK, Bai S, Hu M, Sei E, Wood A, Wiley J, Chen H, Contreras A, Teshome M, Lim B, Navin NE. Towards a human breast cell atlas [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr GS1-02.

Abstract ES5-3: Investigating Breast Cancer with Single-Cell Sequencing

Tumors evolve from single cells. As they evolve, they acquire complex somatic mutations and diversify, forming distinct subpopulations of cells. This intratumor heterogeneity confounds basic research and clinical practice because tools do not exist to resolve it. Standard genomic methods are limited to reporting an average signal from a complex population of cells, because they require a large amount of input material. These bulk methods may mask population diversity and rare cells in the tumor - that may be the most malignant. To address this limitation my laboratory has developed single-cell sequencing tools to delineate intratumor heterogeneity and investigate mutational evolution in human cancers. We developed a method to profile genomic copy number in single cells and used this method to study genome evolution in triple-negative (ER−/PR−/Her2-) breast tumors (Navin et al., 2011 Nature) which revealed a punctuated model for copy number evolution. Recently, we have extended this method to obtain whole-genome, high-coverage sequencing data from single human tumor cells. From this data we can detect the full spectrum of genomic mutations, including point mutations, indels and microdeletions in single human cells. We applied this method to study clonal diversity in an estrogen-receptor-positive breast carcinoma and sequenced four single cells in addition to a population sample. In the population we detected only 36 coding mutations. However, our whole-genome single-cell sequencing data revealed hundreds of additional coding mutations, suggesting extensive clonal diversity in the tumor. Our data from this tumor support a mutator phenotype model for tumor progression, in which cancer is driven by elevating the rate of random mutations. Our studies show that a wealth of information can be obtained from studying single cancer cells, data that could not be obtained by analyzing the tumor en masse. We expect single-cell sequencing to have major clinical applications in early detection, analyzing scarce tissue samples and monitoring residual disease in patients with cancer.

Citation Information: Cancer Res 2012;72(24 Suppl):Abstract nr ES5-3.

Probing WW Domains to Uncover and Refine Determinants of Specificity in Ligand Recognition

Understanding the specificity of protein-protein interaction mediated by domains and their ligands will have strong impact on basic and applied research. Visual inspection of WW domain sequences prompted a general classification of the domains into two large subfamilies. One subfamily contains two consecutive aromatic residues in the beta 2 strand of the domain whereas the other contains three or four consecutive aromatic residues in the same position. In the recent past, we proposed a rule of 'two vs. three aromatics' in the beta 2 strand of WW domains as a molecular discriminator between Class I and Class II WW domains, which recognize PPxY or PPLP motifs, respectively. Using phage display libraries expressing WW domains with random sequences replacing a part of the beta 2 strand, we provided additional evidence supporting our rule. We conclude that three consecutive aromatic amino acids within the beta 2 strand of WW domain are required but not always sufficient for the WW domain to belong to Class II.

High-resolution ROMA CGH and FISH analysis of aneuploid and diploid breast tumors

Combining representational oligonucleotide microarray analysis (ROMA) of tumor DNA with fluorescence in situ hybridization (FISH) of individual tumor cells provides the opportunity to detect and validate a wide range of amplifications, deletions, and rearrangements directly in frozen tumor samples. We have used these combined techniques to examine 101 aneuploid and diploid breast tumors for which long-term follow-up and detailed clinical information were available. We have determined that ROMA provides accurate and sensitive detection of duplications, amplifications, and deletions and yields defined boundaries for these events with a resolution of <50 kbp in most cases. We find that diploid tumors exhibit fewer rearrangements on average than aneuploids, but rearrangements occur at the same locations in both types. Diploid tumors reflect at least three consistent patterns of rearrangement. The reproducibility and frequency of these events, especially in very early stage tumors, provide insight into the earliest chromosomal events in breast cancer. We have also identified correlations between certain sets of rearrangement events and clinically relevant parameters such as long-term survival. These correlations may enable novel prognostic indicators for breast and other cancers as more samples are analyzed.