Publications

Acute kidney injury (AKI) promotes an abrupt loss of kidney function that results in substantial morbidity and mortality. Considerable effort has gone toward identification of diagnostic biomarkers and analysis of AKI-associated molecular events; however, most studies have adopted organ-wide approaches and have not elucidated the interplay among different cell types involved in AKI pathophysiology. To better characterize AKI-associated molecular and cellular events, we developed a mouse line that enables the identification of translational profiles in specific cell types. This strategy relies on CRE recombinase-dependent activation of an EGFP-tagged L10a ribosomal protein subunit, which allows translating ribosome affinity purification (TRAP) of mRNA populations in CRE-expressing cells. Combining this mouse line with cell type-specific CRE-driver lines, we identified distinct cellular responses in an ischemia reperfusion injury (IRI) model of AKI. Twenty-four hours following IRI, distinct translational signatures were identified in the nephron, kidney interstitial cell populations, vascular endothelium, and macrophages/monocytes. Furthermore, TRAP captured known IRI-associated markers, validating this approach. Biological function annotation, canonical pathway analysis, and in situ analysis of identified response genes provided insight into cell-specific injury signatures. Our study provides a deep, cell-based view of early injury-associated molecular events in AKI and documents a versatile, genetic tool to monitor cell-specific and temporal-specific biological processes in disease modeling.

BACKGROUND: The impact of raltegravir-resistant HIV-1 minority variants (MVs) on raltegravir treatment failure is unknown. Illumina sequencing offers greater throughput than 454, but sequence analysis tools for viral sequencing are needed. We evaluated Illumina and 454 for the detection of HIV-1 raltegravir-resistant MVs.

METHODS: A5262 was a single-arm study of raltegravir and darunavir/ritonavir in treatment-naïve patients. Pre-treatment plasma was obtained from 5 participants with raltegravir resistance at the time of virologic failure. A control library was created by pooling integrase clones at predefined proportions. Multiplexed sequencing was performed with Illumina and 454 platforms at comparable costs. Illumina sequence analysis was performed with the novel snp-assess tool and 454 sequencing was analyzed with V-Phaser.

RESULTS: Illumina sequencing resulted in significantly higher sequence coverage and a 0.095% limit of detection. Illumina accurately detected all MVs in the control library at ≥0.5% and 7/10 MVs expected at 0.1%. 454 sequencing failed to detect any MVs at 0.1% with 5 false positive calls. For MVs detected in the patient samples by both 454 and Illumina, the correlation in the detected variant frequencies was high (R2 = 0.92, P<0.001). Illumina sequencing detected 2.4-fold greater nucleotide MVs and 2.9-fold greater amino acid MVs compared to 454. The only raltegravir-resistant MV detected was an E138K mutation in one participant by Illumina sequencing, but not by 454.

CONCLUSIONS: In participants of A5262 with raltegravir resistance at virologic failure, baseline raltegravir-resistant MVs were rarely detected. At comparable costs to 454 sequencing, Illumina demonstrated greater depth of coverage, increased sensitivity for detecting HIV MVs, and fewer false positive variant calls.

Regulated transcription controls the diversity, developmental pathways and spatial organization of the hundreds of cell types that make up a mammal. Using single-molecule cDNA sequencing, we mapped transcription start sites (TSSs) and their usage in human and mouse primary cells, cell lines and tissues to produce a comprehensive overview of mammalian gene expression across the human body. We find that few genes are truly 'housekeeping', whereas many mammalian promoters are composite entities composed of several closely separated TSSs, with independent cell-type-specific expression profiles. TSSs specific to different cell types evolve at different rates, whereas promoters of broadly expressed genes are the most conserved. Promoter-based expression analysis reveals key transcription factors defining cell states and links them to binding-site motifs. The functions of identified novel transcripts can be predicted by coexpression and sample ontology enrichment analyses. The functional annotation of the mammalian genome 5 (FANTOM5) project provides comprehensive expression profiles and functional annotation of mammalian cell-type-specific transcriptomes with wide applications in biomedical research.

In this study, we performed an in-depth characterization of the male pediatric infant urinary proteome by parallel proteomic analysis of normal healthy adult (n=6) and infant (n=6) males and comparison to available published data. A total of 1584 protein groups were identified. Of these, 708 proteins were identified in samples from both cohorts. Although present in both cohorts, 136 of these common proteins were significantly enriched in urine from adults and 94 proteins were significantly enriched in urine from infants. Using Gene Ontology, we found that the infant-enriched or specific subproteome (743 proteins) had an overrepresentation of proteins that are involved in translation and transcription, cellular growth and metabolic processes. In contrast, the adult enriched or specific subproteome (364 proteins) showed an overexpression of proteins involved in immune response and cell adhesion. This study demonstrates that the non-diseased male urinary proteome is quantitatively affected by age, has age-specific subproteomes, and identifies a common subproteome with no age-dependent abundance variations. These findings highlight the importance of age-matching in urinary proteomics. This article is part of a Special Issue entitled: Biomarkers: A Proteomic Challenge.

UNLABELLED: Alternate promoter usage is an important molecular mechanism for generating RNA and protein diversity. Cap Analysis Gene Expression (CAGE) is a powerful approach for revealing the multiplicity of transcription start site (TSS) events across experiments and conditions. An understanding of the dynamics of TSS choice across these conditions requires both sensitive quantification and comparative visualization. We have developed CAGExploreR, an R package to detect and visualize changes in the use of specific TSS in wider promoter regions in the context of changes in overall gene expression when comparing different CAGE samples. These changes provide insight into the modification of transcript isoform generation and regulatory network alterations associated with cell types and conditions. CAGExploreR is based on the FANTOM5 and MPromDb promoter set definitions but can also work with user-supplied regions. The package compares multiple CAGE libraries simultaneously. Supplementary Materials describe methods in detail, and a vignette demonstrates a workflow with a real data example.

AVAILABILITY AND IMPLEMENTATION: The package is freely available under the MIT license from CRAN (http://cran.r-project.org/web/packages/CAGExploreR).

CONTACT: edimont@mail.harvard.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Identifying microRNA (miRNA)-regulated genes is key to understanding miRNA function. However, many miRNA recognition elements (MREs) do not follow canonical "seed" base-pairing rules, making identification of bona fide targets challenging. Here, we apply an unbiased sequencing-based systems approach to characterize miR-522, a member of the oncogenic primate-specific chromosome 19 miRNA cluster, highly expressed in poorly differentiated cancers. To identify miRNA targets, we sequenced full-length transcripts captured by a biotinylated miRNA mimic. Within these targets, mostly noncanonical MREs were identified by sequencing RNase-resistant fragments. miR-522 overexpression reduced mRNA, protein levels, and luciferase activity of >70% of a random list of candidate target genes and MREs. Bioinformatic analysis suggested that miR-522 regulates cell proliferation, detachment, migration, and epithelial-mesenchymal transition. miR-522 induces G1 cell-cycle arrest and causes cells to detach without anoikis, become invasive, and express mesenchymal genes. Thus, our method provides a simple but effective technique for identifying miRNA-regulated genes and biological function.

LIN28 function is fundamental to the activity and behavior of human embryonic stem cells (hESCs) and induced pluripotent stem cells. Its main roles in these cell types are the regulation of translational efficiency and let-7 miRNA maturation. However, LIN28-associated mRNA cargo shifting and resultant regulation of translational efficiency upon the initiation of differentiation remain unknown. An RNA-immunoprecipitation and microarray analysis protocol, eRIP, that has high specificity and sensitivity was developed to test endogenous LIN28-associated mRNA cargo shifting. A combined eRIP and polysome analysis of early stage differentiation of hESCs with two distinct differentiation cues revealed close similarities between the dynamics of LIN28 association and translational modulation of genes involved in the Wnt signaling, cell cycle, RNA metabolism and proteasomal pathways. Our data demonstrate that change in translational efficiency is a major contributor to early stages of differentiation of hESCs, in which LIN28 plays a central role. This implies that eRIP analysis of LIN28-associated RNA cargoes may be used for rapid functional quality control of pluripotent stem cells under manufacture for therapeutic applications.

It is acknowledged that some obesity trajectories are set early in life, and that rapid weight gain in infancy is a risk factor for later development of obesity. Identifying modifiable factors associated with early rapid weight gain is a prerequisite for curtailing the growing worldwide obesity epidemic. Recently, much attention has been given to findings indicating that gut microbiota may play a role in obesity development. We aim at identifying how the development of early gut microbiota is associated with expected infant growth. We developed a novel procedure that allows for the identification of longitudinal gut microbiota patterns (corresponding to the gut ecosystem developing), which are associated with an outcome of interest, while appropriately controlling for the false discovery rate. Our method identified developmental pathways of Staphylococcus species and Escherichia coli that were associated with expected growth, and traditional methods indicated that the detection of Bacteroides species at day 30 was associated with growth. Our method should have wide future applicability for studying gut microbiota, and is particularly important for translational considerations, as it is critical to understand the timing of microbiome transitions prior to attempting to manipulate gut microbiota in early life.

Comparisons of stem cell experiments at both molecular and semantic levels remain challenging due to inconsistencies in results, data formats, and descriptions among biomedical research discoveries. The Harvard Stem Cell Institute (HSCI) has created the Stem Cell Commons (stemcellcommons.org), an open, community-based approach to data sharing. Experimental information is integrated using the Investigation-Study-Assay tabular format (ISA-Tab) used by over 30 organizations (ISA Commons, isacommons.org). The early adoption of this format permitted the novel integration of three independent systems to facilitate stem cell data storage, exchange and analysis: the Blood Genomics Repository, the Stem Cell Discovery Engine, and the new Refinery platform that links the Galaxy analytical engine to data repositories.