Structural analysis of the female reptile reproductive system by micro-computed tomography and optical coherence tomography†.

Volumetric data provide unprecedented structural insight to the reproductive tract and add vital anatomical context to the relationships between organs. The morphology of the female reproductive tract in non-avian reptiles varies between species, corresponding to a broad range of reproductive modes and providing valuable insight to comparative investigations of reproductive anatomy. However, reproductive studies in reptilian models, such as the brown anole studied here, have historically relied on histological methods to understand the anatomy. While these methods are highly effective for characterizing the cell types present in each organ, histological methods lose the 3D relationships between images and leave the architecture of the organ system poorly understood. We present the first comprehensive volumetric analyses of the female brown anole reproductive tract using two non-invasive, non-destructive imaging modalities: micro-computed tomography (microCT) and optical coherence tomography (OCT). Both are specialized imaging technologies that facilitate high-throughput imaging and preserve three-dimensional information. This study represents the first time that microCT has been used to study all reproductive organs in this species and the very first time that OCT has been applied to this species. We show how the non-destructive volumetric imaging provided by each modality reveals anatomical context including orientation and relationships between reproductive organs of the anole lizard. In addition to broad patterns of morphology, both imaging modalities provide the high resolution necessary to capture details and key anatomical features of each organ. We demonstrate that classic histological features can be appreciated within whole-organ architecture in volumetric imaging using microCT and OCT, providing the complementary information necessary to understand the relationships between tissues and organs in the reproductive system. This side-by-side imaging analysis using microCT and OCT allows us to evaluate the specific advantages and limitations of these two methods for the female reptile reproductive system.

Fully Automated Sample Processing and Analysis Workflow for Low-Input Proteome Profiling.

Recent advances in sample preparation and analysis have enabled direct profiling of protein expression in single mammalian cells and other trace samples. Several techniques to prepare and analyze low-input samples employ custom fluidics for nanoliter sample processing and manual sample injection onto a specialized separation column. While being effective, these highly specialized systems require significant expertise to fabricate and operate, which has greatly limited implementation in most proteomic laboratories. Here, we report a fully automated platform termed autoPOTS (automated preparation in one pot for trace samples) that uses only commercially available instrumentation for sample processing and analysis. An unmodified, low-cost commercial robotic pipetting platform was utilized for one-pot sample preparation. We used low-volume 384-well plates and periodically added water or buffer to the microwells to compensate for limited evaporation during sample incubation. Prepared samples were analyzed directly from the well plate with a commercial autosampler that was modified with a 10-port valve for compatibility with 30 µm i.d. nanoLC columns. We used autoPOTS to analyze 1-500 HeLa cells and observed only a moderate reduction in peptide coverage for 150 cells and a 24% reduction in coverage for single cells compared to our previously developed nanoPOTS platform. To evaluate clinical feasibility, we identified an average of 1095 protein groups from ∼130 sorted B or T lymphocytes. We anticipate that the straightforward implementation of autoPOTS will make it an attractive option for low-input and single-cell proteomics in many laboratories.

Simple and Efficient Data Analysis Dissemination for Individual Laboratories.

Scientific progress comes as we build upon the work of others. Implicit in this advance is that we have access to and can thoroughly examine the work of others. It is important to recognize that our scholarly work as scientists encompasses not only experimental design and data collection but also our analytical methods. Thus when communicating biology experiments, especially those that utilize molecular omics data, the analysis methods that connect raw data to scientific conclusions must be presented with sufficient clarity that others can reproduce our exact work. Although there are many resources for sharing raw data files, there is currently not a widely utilized method for sharing analysis methods. We present a semistructured pattern for sharing analysis methods that is simple and efficient and can be implemented by individual laboratories using existing software. This pattern requires three types of files in a publicly accessible repository, such as GitHub: (1) data files, (2) a universal I/O script that parses all data files, and (3) analysis scripts creating figures and metrics reported in the manuscript. We suggest additional conventions to improve the readability and provide a template repository for the pattern. Sharing our exact analysis methods as software, in addition to their narrative description in a manuscript, will ensure reproducibility and transparency. Importantly, the pattern we present does not require new infrastructure and can be achieved without advanced computing skills.