This report houses:

  1. proteomics table for DIA MS/MS analysis for two ATCC cell line derived EVs.

  2. tables for LnCAP (prostate carcinoma) EV derived small RNA (miRNA and genic) sequencing tables from 2 facilities (A and B), and

  3. comparison with EVAtlas database for miRNAs.

EV-associated marker protein identified in two cell types from ATCC in DIA-MS analysis


Table I: Differential Expression profies of EV associate proteins from two ATCC cell lines

EV_associated_protein_expression_table<-read.csv("D:/ATCC_paper/Seq_Rfiles/ATCC Protein Map Data_revised.csv")
EV_associated_protein_expression_table

There were 131 differential expression of EV-associated/marker proteins in two cell types from ATCC (hTERT MSC: hTERT-immortalized mesenchymal stem cells, and LNCaP: prostate carcinoma) using normalized protein Q-values.

miRNA tables and comparison with EVAtlas miRNA database


Table II: Facility A mean normalized expression, miRNA identified and relative expression in samples 1, 2, 3, and 4

facilityA_miRNA_table<-read.csv("D:/ATCC_paper/Seq_Rfiles/FacilityA_miRNA.csv")
facilityA_miRNA_table


Table III: Facility B mean normalized expression, miRNA identified and relative expression in samples 1, 2, 3, and 4

facilityB_miRNA_table<-read.csv("D:/ATCC_paper/Seq_Rfiles/FacilityB_miRNA.csv")
facilityB_miRNA_table


Table IV: Common miRNAs from Facility A and B, and their relative expression in samples 1, 2, 3, and 4

common_miRNAs_overlapping<-read.csv("D:/ATCC_paper/Seq_Rfiles/Overlap_miRNA_DEseq2-normalized.csv")
common_miRNAs_overlapping

There were 485 distinct miRNAs that were common in both facilities.

n_distinct(common_miRNAs_overlapping$miRNA)
## [1] 485


Table V: Unique miRNAs from Facility A and B, and their relative expression in samples 1, 2, 3, and 4

merged_table_miRNA <- merge(facilityA_miRNA_table, facilityB_miRNA_table, by = "miRNA", all=TRUE)
merged_table_miRNA

There were total 949 miRNAs that were unique when data from both facilities were combined.

n_distinct(merged_table_miRNA$miRNA)
## [1] 949

We compared the 949 miRNAs to an available EV miRNA database called EVAtlas [1].


Table VI: EVAtlas miRNA database

funrich<-read.table(file = 'D:/ATCC_paper/Seq_Rfiles/miRNAFunRich.txt', sep = '\t', header = TRUE)
funrich


Table VII: Comparison of unique miRNAs from facilities A and B with EVAtlas miRNAs

merged_table_funrich <- merge(x=merged_table_miRNA[, c("miRNA", "FacilityA_1_EV")], 
                       y=funrich[, c("miRNA.product", "miRNA.family")], 
                       by.x = "miRNA", by.y = "miRNA.product")%>%
distinct()
merged_table_funrich

We identified 952 miRNAs that overlapped with EVAtlas database, although only 949 unique miRNAs were identified from two facilities. All miRNAs overlapped with the database and 3 miRNAs were duplicated in this analysis (see Table VIII).


Table VIII: Duplicated miRNAs in comprison of EVAtlas database with total unique miRNAs from Facility A and B

df<-merged_table_funrich[duplicated(merged_table_funrich$miRNA),]
df

Small mRNA (genic) tables from facilities A and B


Table IX: Facility A genic mean normalized expression, small mRNA identified and relative expression in samples 1, 2, 3, and 4

facilityA_genic_mRNA_table<-read.csv("D:/ATCC_paper/Seq_Rfiles/FacilityA_genic_mRNA.csv")
facilityA_genic_mRNA_table


Table X : Facility B genic mean normalized expression, small mRNA identified and relative expression in samples 1, 2, 3, and 4

facilityB_genic_mRNA_table<-read.csv("D:/ATCC_paper/Seq_Rfiles/FacilityB_genic_mRNA.csv")
facilityB_genic_mRNA_table


Table XI: Common miRNAs from Facility A and B, and their relative expression in samples 1, 2, 3, and 4

common_genic_mRNAs_overlapping<-read.csv("D:/ATCC_paper/Seq_Rfiles/Overlap_gene_DEseq2-normalized.csv")
common_genic_mRNAs_overlapping

33 distinct common small RNA were identified in analysis of facility A and B sequencing results.

n_distinct(common_genic_mRNAs_overlapping$gene)
## [1] 33


Table XII: Unique mRNAs from Facility A and B, and their relative expression in samples 1, 2, 3, and 4

merged_table_mRNA <- merge(facilityA_genic_mRNA_table, facilityB_genic_mRNA_table, by = "gene", all=TRUE)
merged_table_mRNA

445 total distinct small mRNA (genic) were identified from facilities A and B.

n_distinct(merged_table_mRNA$gene)
## [1] 445