We would like to thank Alison French at NASA Ames Life Science Data Archive for her assistance with obtaining the video related to the Rodent Habitats and overall help with obtaining cage related information. We also like to thank Marla Smithwick at NASA Ames Research Center for her help with obtaining the proper information. Research funding was provided by the GeneLab Project at NASA Ames Research Center, through NASA's Space Biology Program in the Division of Space Life and Physical Sciences Research and Applications (SLPSRA). Any use of trade names is for descriptive purposes only and does not imply endorsement by the US Government.

The authors have nothing to disclose.

The NASA GeneLab platform is a comprehensive omics database and analysis platform that will allow the scientific community to generate novel hypotheses related to space biology. Here we have presented a comprehensive procedure for rodent experiments from the beginning of spaceflight to the generation of novel hypothesis from analyzing data utilizing a publicly available space biology platform. In addition, we have also provided an extensive protocol on an unbiased systems biology analysis for identifying key genes driving the system being studied. We have used our recent study36 as an example of how this protocol is effectively utilized to generate a novel hypothesis for space biology. We hope that this helps investigators better understand how spaceflight experiments are performed and how data from them lead to the data available on GeneLab, and ultimately allow for clearer interpretation of publicly available space biology omics data.
There are several critical steps within our protocol regarding both rodent spaceflight experiments and analysis of the data produced. Understanding the Rodent Habitat setup is critical to develop and design the optimal experiment for spaceflight. This would specifically entail the protocol and description we have provided in step 1 of our protocol. Once an investigator fully understands the different conditions existing in the Rodent Habitats compared to vivarium cages, the biological results being interpreted can be correlated properly to the environmental conditions in space. In additions, modifications to the Rodent Habitat cannot be done, since the Rodent Habitat has been optimally designed and approved by NASA for use of spaceflight.
To interpret the biological results, we have provided a thorough protocol on every step involved from uploading your data to GeneLab to analysis of the data to generate novel space biology hypothesis. Although all the steps are important in understanding how to generate data, the most critical steps for data analysis are steps 9 and 10. Step 9 provides a protocol to analyze transcriptomic data using an unbiased systems biology method to determine genes/pathways that are truly driving the experimental condition being analyzed. Step 10 is critical as it provides users with an easy methodology to analyze omics GeneLab datasets using the GeneLab platform. Modifications to the protocol provided can be done for some steps regarding analyzing data. Specifically, steps 9.4&#8211;9.6 can be done using R programming or any other favorite tools that the user prefers. Depending on the dataset, different statistics and fold-change cutoffs can be used to determine the significantly regulated genes. In addition, for determining the key genes in steps 9.5 and 9.6, the user can modify this protocol and use any tool that utilizes the significantly regulated genes to predict functions. The important concept is that using multiple predictive functional omics tools allows for determination of genes involved with the majority of functions being regulated in the system being studied.
The GeneLab platform continues to develop, and while the analyses described here were performed after data download, the next phase of GeneLab will allow for analysis of omics data directly on GeneLab platform, which will provide an easy workflow to generate processed data for higher-order analysis. Moreover, whereas we have focused on a protocol for interpreting transcriptomic data, GeneLab contains a wide variety of omics data including proteomic, genomic, metabolomic, and epigenomic data. The eventual platform will contain pipelines and guidelines for analysis of these different types of omics. The last phase of GeneLab will also implement a system level visualization interface to allow the basic user to easily generate space biology hypotheses.
Lastly, our systems biology analysis provides a unique and unbiased method to determine the key driving genes/pathways in any system being studied using omics datasets. We have used this methodology in several different independent studies with great success to determine the key drivers involved36,45,46,47,48,49,50. In a cancer related omics study, using this methodology we experimentally validated that our predicted key genes/pathways were actually driving the drug treatment response by knocking out the key genes in vitro45. We observed, as we had predicted through this protocol, that the treatment was not effective anymore due to the absence of the key genes. We believe that this unbiased systems biology protocol can be a useful tool to determine key pathways for any omics study.
This protocol provides a quick and efficient method for the generation of novel space biology hypotheses. The data generated from GeneLab can be leveraged by investigators for future funding opportunities, experimental validation, and potential targets for development of countermeasures against microgravity and space radiation. The protocol provided here will permit for future space biology investigations to occur with optimal efficiency to allow for safe long-term space missions.

The overall goal of this manuscript is to provide a clear methodology of how to use NASA&#39;s GeneLab platform1 and how rodent experiments done in space are translated to omics data for analysis. Spacefaring humans are exposed to numerous health risks from altered gravity fields, space radiation, isolation from Earth, and other hostile environmental factors2,3,4,5,6. Biological experiments performed in space and on the ground have helped to define and quantify these risks7,8,9,10,11,12,13,14. In space, these experiments have been conducted on the International Space Station (ISS), the Space Shuttle, and other orbital platforms. Conducting these experiments requires specialized hardware and methodology given the unique concerns of performing experiments in space including limited crew time and the microgravity environment. Various platforms now exist for performing sophisticated experiments in space using plant, animal, and microbial models15.
Rodent models have been particularly important to advancing our understanding of how mammals, including humans, respond to spaceflight. These include the impact of spaceflight on the muscle structure16,17,18 and immune functions19,20,21. The standard vivarium cages used for housing rodents on Earth are not suitable for spaceflight experiments22,23. Therefore, over the years mice and rats have been flown and housed in various cages including the Japanese Aerospace Exploration Agency (JAXA) Habitat Cage24, animal carrying space capsules used on the BION-M1 unmanned Russian satellite25,26,27, the Mice Drawer System (MDS) designed by the Italian Space Agency28,29,30, the NASA Animal Enclosure Module (AEM), and now the NASA Rodent Transporter and Habitats23. Rodent experiments first started on board the Space Shuttle using cages referred to as the Animal Enclosure Module (AEM). This hardware was used in 27 rodent experiments on the Space Shuttle23. The AEM was originally developed for relatively short experiments on-board the shuttle (&#60; 20 days). Since the development of the ISS, the AEMs have been modified for longer duration experiments and are now referred to as Rodent Habitats22,23. The new Rodent Habitats are designed to support long-duration missions in the ISS using the EXpedite the PRocessing of Experiments for Space Station (EXPRESS) Rack interface. Rodent Habitats are substantially different from standard vivarium cages in their dimensions, air flow, filter and exhaust system, and access to food and water (Figure 1). Nevertheless, this hardware has proven to be an effective research platform, enabling key insights into the spaceflight-induced changes to mammalian physiology19,31,32,33,34,35,36.
Large volumes of omics data can now be generated from biological spaceflight experiments including those performed with rodents. Recently, data from these omics experiments have been made publicly available through the NASA GeneLab platform1 which is a comprehensive data repository and analysis platform that allows anyone to develop hypotheses from spaceflight experiments. GeneLab provides tools for the discovery, access, sharing and analysis of data. We utilized GeneLab datasets to show that differences between the standard vivarium cages and specialized Rodent Habitats used in space cause massive differences in the transcriptome of mice36. We analyzed four different publicly available datasets, comparing different tissues from rodents housed in either the Rodent Habitats or standard vivarium cages. Using an unbiased systems biology analysis, we determined that the main drivers and pathways that were changed were consistent with a hypoxic response due to the high CO2 levels caused by higher CO2 concentrations on ISS, which leads to higher CO2 concentrations in the Rodent Habitat given that they are passive systems that take in the ambient air. This demonstrates how scientists can use open source tools and data to generate novel findings with implication on how the environment of the ISS impacts astronaut health.
Here we describe how rodent experiments are performed in space and how data from these experiments can be accessed through an open-source, omic platform related to space biology. We discuss the configuration of the Rodent Habitats used for space missions, and how spaceflight tissues are processed. We also describe how spaceflight omics data can be discovered and accessed on GeneLab and how key factors driving the overall response to spaceflight can be identified36. The specific example we will present on how this protocol is implemented will be comparing the biological differences occurring in rodents housed in Rodent Habitat and the vivarium controls that were published by Beheshti et al.36. It is important to note that ground controls are essential for spaceflight rodent experiments. As described in this protocol, these controls are done with both identical conditions (i.e., CO2 conditions, humidity, temperature, cage dimensions, etc.) in the Rodent Habitats on the ISS and in standard vivarium cages that have the standard environmental (i.e., CO2 conditions, humidity, and temperature) conditions on Earth. The rodents housed in the Rodent Habitat ground controls allow for the direct comparison to rodents in space. While rodents housed in vivarium cages allow for the biological comparison between the different housing (e.g., vivarium cages vs. Rodent hardware). The Rodent Habitat is different than vivarium cages in that it has constant air flow (0.1&#8211;0.3 m/s), a long duration, and a secondary exhaust filter that captures and absorbs the animal waste guided to the exhaust filter by continuous air flow in microgravity. In addition, Rodent Habitats have passive systems and intake ambient air; therefore, they also have higher CO2 concentrations due to elevated levels in the ISS cabin (~5,000 ppm).

<table border="0" cellpadding="0" cellspacing="0" style="width:720px;" width="721">
	<tbody>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">C57BL/6 Mice</td>
			<td style="width:219px;">The Jackson Laboratoy</td>
			<td style="width:119px;">C57BL/6J</td>
			<td style="width:167px;">C57BL/6 mice were used for datasets related to Rodent Research-1 experiments</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">BALB/C Mice</td>
			<td style="width:219px;">Taconic</td>
			<td style="width:119px;">BALB</td>
			<td>BALB/C mice were used for datasets related to Rodent Research-3 experiments</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Vivarium Cages</td>
			<td style="width:219px;">Charles River Laboratory</td>
			<td style="width:119px;"></td>
			<td>Standard murine cages purchased from Charles River Laboratory</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Rodent Habitat</td>
			<td style="width:219px;">NASA</td>
			<td style="width:119px;"></td>
			<td>This cage and all components are built internally at NASA</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">RNAlater</td>
			<td style="width:219px;">ThermoFisher Scientific</td>
			<td style="width:119px;">AM7020</td>
			<td>RNAlater is used to store the tissue for further RNA isolation</td>
		</tr>
	</tbody>
</table>

exploring the effects of spaceflight on mouse physiology using the open access nasa genelab platform

Performing biological experiments in space requires special accommodations and procedures to ensure that these investigations are performed effectively and efficiently. Moreover, given the infrequency of these experiments it is imperative that their impacts be maximized. The rapid advancement of omics technologies offers an opportunity to dramatically increase the volume of data produced from precious spaceflight specimens. To capitalize on this, NASA has developed the GeneLab platform to provide unrestricted access to spaceflight omics data and encourage its widespread analysis. Rodents (both rats and mice) are common model organisms used by scientists to investigate space-related biological impacts. The enclosure that house rodents during spaceflight are called Rodent Habitats (formerly Animal Enclosure Modules), and are substantially different from standard vivarium cages in their dimensions, air flow, and access to water and food. In addition, due to environmental and atmospheric conditions on the International Space Station (ISS), animals are exposed to a higher CO2 concentration. We recently reported that mice in the Rodent Habitats experience large changes in their transcriptome irrespective of whether animals were on the ground or in space. Furthermore, these changes were consistent with a hypoxic response, potentially driven by higher CO2 concentrations. Here we describe how a typical rodent experiment is performed in space, how omics data from these experiments can be accessed through the GeneLab platform, and how to identify key factors in this data. Using this process, any individual can make critical discoveries that could change the design of future space missions and activities.

Determining key drivers from spaceflight transcriptomic data will assist NASA with determining health risks and developing potential countermeasures to combat negative effects on astronaut health. In our recent publication, we have followed the steps above and utilized GeneLab datasets to successfully show a novel finding that CO2 concentrations on the ISS can impact health36. We have also used the technique above in other studies to successfully determine the key factors driving the system being studied45,46,47,48,49,50. Here we will show how the results from using this protocol can be successfully used to determine the key drivers.
In this study, we primarily focused on the biological differences that occur in rodents housed in the Rodent Habits ground controls and the vivarium controls. As described above, it is the key to better understanding these two habitats, which will provide us information on possible confounding factors that can impact health due to the environment on the ISS. For all rodent spaceflight experiments, these ground controls are also essential to determine which biological factors are associated directly with spaceflight or due to the environmental conditions on the ISS. As stated in the protocol, the environmental condition for the vivarium habitat is not exposed to the higher CO2 level that is present for the Rodent Habitat. The vivarium habitat has the normal CO2 level that is present on Earth (currently being 300 to 380 ppm). The temperature and humidity for both habitats are similar.
We used the following datasets from the GeneLab platform to determine the key genes between the rodents housed in the Rodent Habitat ground controls and vivarium ground controls that are responsible for driving the differences between the two habitats: GLDS-21, GLDS-111, GLDS-25, and GLDS-63. Analysis to determine the significant genes was carried out as described above between the Rodent Habitat (previously AEM) and vivarium controls independently for each dataset. PCA plots showed grouping of the biological replicates (Figure 4 shows the PCA plots for GLDS-21). From the pre-processed data, we determined the leading-edge genes from the different GSEA gene sets. Using the genes with 1.2-fold-change (log2), we were able to predict the genes involved with predictions for upstream regulators, canonical pathways, and biofunctions. For each dataset we then found the common/overlapping genes involved for all the genes (Figure 5). These genes are now believed to be driving the response between the rodents in the Rodent Habitats (or AEM) and vivarium controls. Network representation of how these key genes connect shows the central hubs for each dataset being analyzed (Figure 6). For example, MAPK1 is the central hub for STS-108 skeletal muscle tissues from mice (Figure 6A). This would be interpreted as the gene that is driving the key genes and most likely the central player for causing biological differences for mice housed in Rodent Habitats versus the vivarium cages. In our previous work, we discuss how these key genes are associated with CO2 response from the existing scientific literature and how these genes can be responsible for biological changes observed in the mice36.
Taking a systems biology approach, we next determined a &#34;master regulator&#34; that connects all the datasets/tissues and is potentially responsible for universal biological effects in rodents housed in AEMs compared to vivarium cages. This was done by determining the gene from all the datasets that is the most connected when constructing a network from all the key genes. We were able to show that MAPK1 is the most connected gene and central hub from all the key genes (Figure 7). To confirm if MAPK1 might be responsible for biological changes in mice from the higher CO2 levels in AEMs, we looked through the scientific literature for supporting evidence. We found several studies indicating the correlation of MAPK1 with CO259 and hypoxia19,60,61.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/58447/58447fig1.jpg" /> 
Figure 1: The Rodent Habitat (previously AEM) compared to the vivarium cages.&#160;(A) Image of the AEM cage provided by NASA (Credits: NASA/Dominic Hart). (B) The standard vivarium cage that is currently used (photo taken by our laboratory). This figure has been modified from Beheshti et al.36. <a href="https://jove.unicartagenaproxy.elogim.com/files/ftp_upload/58447/58447fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/58447/58447fig2.jpg" /> 
Figure 2: The Rodent Habitat Hardware System with the three different modules involved during transportation to and from the space missions. The left module (A) is the Rodent Habitat module (previously AEM), the center module (B) is the Transporter, and the right module (C) is the Animal Access Unit (AAU). (D)The&#160;Mouse Transfer Box (MTB). (Credits: NASA/Dominic Hart). <a href="https://jove.unicartagenaproxy.elogim.com/files/ftp_upload/58447/58447fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/58447/58447fig3.jpg" /> 
Figure 3:&#160;Example analysis workflow which can be used in the GeneLab Galaxy interface to process RNA-seq data. <a href="https://jove.unicartagenaproxy.elogim.com/files/ftp_upload/58447/58447fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/58447/58447fig4.jpg" /> 
Figure 4: Principal component analysis (PCA) of representative dataset after pre-processing steps. GLDS-21 dataset for AEM vs. vivarium cage is shown for the murine skeletal muscle from the STS-118 mission. <a href="https://jove.unicartagenaproxy.elogim.com/files/ftp_upload/58447/58447fig4large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/58447/58447fig5.jpg" /> 
Figure 5:&#160;Venn diagram representing what key genes are determined using different pathway prediction tools. <a href="https://jove.unicartagenaproxy.elogim.com/files/ftp_upload/58447/58447fig5large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 6" class="xfigimg" src="/files/ftp_upload/58447/58447fig6.jpg" /> 
Figure 6: The key genes determined for all conditions and murine tissues between the AEM vs. vivarium cages.&#160;(A-E) Network representation of the key genes for each dataset/rodent tissue. Log2 fold-changes (with a cutoff of 1.2-fold-change) to the gene expression were used to obtain different shades of green for fold-change in downregulated genes, while different shades of red depict fold-change in upregulated genes. The darker the shade of green or red, the greater the fold-change. This figure has been modified from Beheshti et al.36. <a href="https://jove.unicartagenaproxy.elogim.com/files/ftp_upload/58447/58447fig6large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 7" class="xfigimg" src="/files/ftp_upload/58447/58447fig7.jpg" /> 
Figure 7: Determining the &#34;master regulator&#34; for rodents in Rodent Habitat housing compared to vivarium cages. Connections between all individual key genes (Figure 6) were determined and displayed as a network through IPA. Network is represented as a radial plot with the most connected key gene, MAPK1, in the center. <a href="https://jove.unicartagenaproxy.elogim.com/files/ftp_upload/58447/58447fig7large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
Supplemental Figure 1: GeneLab-GenomeSpace Integration with ISACreator for Streamlining Data Processing Operations.&#160;&#160;<a href="https://jove.unicartagenaproxy.elogim.com/files/ftp_upload/58447/Supplemental_Figure_1.tif" target="_blank">Please click here to download this figure.</a>
Supplemental Figure 2: Screenshot of GeneLab searches using federation/integration with heterogeneous bioinformatics external databases (GEO, PRIDE, MG-RAST).&#160;<a href="https://jove.unicartagenaproxy.elogim.com/files/ftp_upload/58447/Supplemental_Figure_2.tif" target="_blank">Please click here to download this figure</a>
Supplemental Figure 3: Screenshot of the GeneLab collaborative workspace showing the user account management, and access controls (e.g., private, shared, public folders).&#160;<a href="https://jove.unicartagenaproxy.elogim.com/files/ftp_upload/58447/Supplemental_Figure_3.tif" target="_blank">Please click here to download this figure</a>

Watch this Scientific Journal Video about Exploring the Effects of Spaceflight on Mouse Physiology using the Open Access NASA GeneLab Platform at JoVE.com

Exploring the Effects of Spaceflight on Mouse Physiology using the Open Access NASA GeneLab Platform

The NASA GeneLab platform provides unfettered access to precious omics data from biological spaceflight experiments. We describe how a typical mouse experiment is conducted in space and how data from such experiments can be accessed and analyzed.

Performing biological experiments in space requires special accommodations and procedures to ensure that these investigations are performed effectively ...

exploring-effects-spaceflight-on-mouse-physiology-using-open-access

Universidad de Cartagena UDEC

Research

JoVE Journal

Genetics

12.2K Views.  NASA Ames Research Center. The NASA GeneLab platform provides unfettered access to precious omics data from biological spaceflight experiments. We describe how a typical mouse experiment is conducted in space and how data from such experiments can be accessed and analyzed.

Video: Exploring the Effects of Spaceflight on Mouse Physiology using the Open Access NASA GeneLab Platform

The Visual Colorimetric Detection of Multi-nucleotide Polymorphisms on a Pneumatic Droplet Manipulation Platform

A simple and visual method to detect multi-nucleotide polymorphism (MNP) was performed on a pneumatic droplet manipulation platform on an open surface. This approach to colorimetric DNA detection was based on the hybridization-mediated growth of gold nanoparticle probes (AuNP probes). The growth size and configuration of the AuNP are dominated by the number of DNA samples hybridized with the probes. Based on the specific size- and shape-dependent optical properties of the nanoparticles, the number of mismatches in a sample DNA fragment to the probes is able to be discriminated. The tests were conducted via droplets containing reagents and DNA samples respectively, and were transported and mixed on the pneumatic platform with the controlled pneumatic suction of the flexible PDMS-based superhydrophobic membrane. Droplets can be delivered simultaneously and precisely on an open-surface on the proposed pneumatic platform that is highly biocompatible with no side effect of DNA samples inside the droplets. Combining the two proposed methods, the multi-nucleotide polymorphism can be detected at sight on the pneumatic droplet manipulation platform; no additional instrument is required. The procedure from installing the droplets on the platform to the final result takes less than 5 min, much less than with existing methods. Moreover, this combined MNP detection approach requires a sample volume of only 10 &#181;l in each operation, which is remarkably less than that of a macro system.

This work presents a simple and visual method to detect multi-nucleotide polymorphisms on a pneumatic droplet manipulation platform. With the proposed method, the entire experiment, including droplet manipulation and detection of multi-nucleotide polymorphisms, can be performed near 23 &#176;C without the aid of advanced instruments.

A simple and visual method to detect multi-nucleotide polymorphism (MNP) was performed on a pneumatic droplet manipulation platform on an open surface. ...

Conjugative Mating Assays for Sequence-specific Analysis of Transfer Proteins Involved in Bacterial Conjugation

The transfer of genetic material by bacterial conjugation is a process that takes place via complexes formed by specific transfer proteins. In Escherichia coli, these transfer proteins make up a DNA transfer machinery known as the mating pair formation, or DNA transfer complex, which facilitates conjugative plasmid transfer. The objective of this paper is to provide a method that can be used to determine the role of a specific transfer protein that is involved in conjugation using a series of deletions and/or point mutations in combination with mating assays. The target gene is knocked out on the conjugative plasmid and is then provided in trans through the use of a small recovery plasmid harboring the target gene. Mutations affecting the target gene on the recovery plasmid can reveal information about functional aspects of the target protein that result in the alteration of mating efficiency of donor cells harboring the mutated gene. Alterations in mating efficiency provide insight into the role and importance of the particular transfer protein, or a region therein, in facilitating conjugative DNA transfer. Coupling this mating assay with detailed three-dimensional structural studies will provide a comprehensive understanding of the function of the conjugative transfer protein as well as provide a means for identifying and characterizing regions of protein-protein interaction.

Here, we present a protocol to knockout a gene of interest involved in plasmid conjugation and subsequently analyze the impact of its absence using mating assays. The function of the gene is further explored to a specific region of its sequence using deletion or point mutations.

The transfer of genetic material by bacterial conjugation is a process that takes place via complexes formed by specific transfer proteins. In Escherichia ...

Systemic Delivery of MicroRNA Using Recombinant Adeno-associated Virus Serotype 9 to Treat Neuromuscular Diseases in Rodents

RNA interference via the endogenous miRNA pathway regulates gene expression by controlling protein synthesis through post-transcriptional gene silencing. In recent years, miRNA-mediated gene regulation has shown potential for treatment of neurological disorders caused by a toxic gain of function mechanism. However, efficient delivery to target tissues has limited its application. Here we used a transgenic mouse model for spinal and bulbar muscular atrophy (SBMA), a neuromuscular disease caused by polyglutamine expansion in the androgen receptor (AR), to test gene silencing by a newly identified AR-targeting miRNA, miR-298. We overexpressed miR-298 using a recombinant adeno-associated virus (rAAV) serotype 9 vector to facilitate transduction of non-dividing cells. A single tail-vein injection in SBMA mice induced sustained and widespread overexpression of miR-298 in skeletal muscle and motor neurons and resulted in amelioration of the neuromuscular phenotype in the mice.

Here we describe the delivery of microRNA using a recombinant adeno-associated virus serotype 9 in a mouse model of a neuromuscular disease. A single peripheral administration in mice resulted in sustained miRNA overexpression in muscle and motor neurons, providing an opportunity to study miRNA function and therapeutic potential in vivo.

RNA interference via the endogenous miRNA pathway regulates gene expression by controlling protein synthesis through post-transcriptional gene silencing. ...

Studying Cell Cycle-regulated Gene Expression by Two Complementary Cell Synchronization Protocols

The gene expression program of the cell cycle represents a critical step for understanding cell cycle-dependent processes and their role in diseases such as cancer. Cell cycle-regulated gene expression analysis depends on cell synchronization into specific phases. Here we describe a method utilizing two complementary synchronization protocols that is commonly used for studying periodic variation of gene expression during the cell cycle. Both procedures are based on transiently blocking the cell cycle in one defined point. The synchronization protocol by hydroxyurea (HU) treatment leads to cellular arrest in late G1/early S phase, and release from HU-mediated arrest provides a cellular population uniformly progressing through S and G2/M. The synchronization protocol by thymidine and nocodazole (Thy-Noc) treatment blocks cells in early mitosis, and release from Thy-Noc mediated arrest provides a synchronized cellular population suitable for G1 phase and S phase-entry studies. Application of both procedures requires monitoring of the cell cycle distribution profiles, which is typically performed after propidium iodide (PI) staining of the cells and flow cytometry-mediated analysis of DNA content. We show that the combined use of two synchronization protocols is a robust approach to clearly determine the transcriptional profiles of genes that are differentially regulated in the cell cycle (i.e. E2F1 and E2F7), and consequently to have a better understanding of their role in cell cycle processes. Furthermore, we show that this approach is useful for the study of mechanisms underlying drug-based therapies (i.e. mitomycin C, an anticancer agent), because it allows to discriminate genes that are responsive to the genotoxic agent from those solely affected by cell cycle perturbations imposed by the agent.

We report two cell synchronization protocols that provide a context for studying events related to specific phases of the cell cycle. We show that this approach is useful for analyzing the regulation of specific genes in an unperturbed cell cycle or upon exposure to agents affecting the cell cycle.

The gene expression program of the cell cycle represents a critical step for understanding cell cycle-dependent processes and their role in diseases such ...

Using Mouse Oocytes to Assess Human Gene Function During Meiosis I

Embryonic aneuploidy is the major genetic cause of infertility in humans. Most of these events originate during female meiosis, and albeit positively correlated with maternal age, age alone is not always predictive of the risk of generating an aneuploid embryo. Therefore, gene variants might account for incorrect chromosome segregation during oogenesis. Given that access to human oocytes is limited for research purposes, a series of assays were developed to study human gene function during meiosis I using mouse oocytes. First, messenger RNA (mRNA) of the gene and gene variant of interest are microinjected into prophase I-arrested mouse oocytes. After allowing time for expression, oocytes are synchronously released into meiotic maturation to complete meiosis I. By tagging the mRNA with a sequence of a fluorescent reporter, such as green fluorescent protein (Gfp), the localization of the human protein can be assessed in addition to the phenotypic alterations. For example, gain or loss of function can be investigated by establishing experimental conditions that challenge the gene product to fix meiotic errors. Although this system is advantageous in investigating human protein function during oogenesis, adequate interpretation of results should be undertaken given that protein expression is not at endogenous levels and, unless controlled for (i.e. knocked out or down), murine homologs are also present in the system.

As the genetic variants associated with human disease begin to become uncovered, it is becoming increasingly important to develop systems with which to rapidly evaluate the biological significance of those identified variants. This protocol describes methods for evaluating human gene function during female meiosis I using mouse oocytes.

Embryonic aneuploidy is the major genetic cause of infertility in humans. Most of these events originate during female meiosis, and albeit positively ...

Exploring the Root Microbiome: Extracting Bacterial Community Data from the Soil, Rhizosphere, and Root Endosphere

The intimate interaction between plant host and associated microorganisms is crucial in determining plant fitness, and can foster improved tolerance to abiotic stresses and diseases. As the plant microbiome can be highly complex, low-cost, high-throughput methods such as amplicon-based sequencing of the 16S rRNA gene are often preferred for characterizing its microbial composition and diversity. However, the selection of appropriate methodology when conducting such experiments is critical for reducing biases that can make analysis and comparisons between samples and studies difficult. This protocol describes in detail a standardized methodology for the collection and extraction of DNA from soil, rhizosphere, and root samples. Additionally, we highlight a well-established 16S rRNA amplicon sequencing pipeline that allows for the exploration of the composition of bacterial communities in these samples, and can easily be adapted for other marker genes. This pipeline has been validated for a variety of plant species, including sorghum, maize, wheat, strawberry, and agave, and can help overcome issues associated with the contamination from plant organelles.

Here, we describe a protocol to obtain amplicon sequence data of soil, rhizosphere, and root endosphere microbiomes. This information can be used to investigate the composition and diversity of plant-associated microbial communities, and is suitable for the use with a wide range of plant species.

The intimate interaction between plant host and associated microorganisms is crucial in determining plant fitness, and can foster improved tolerance to ...

The Use of Mouse Splenocytes to Assess Pathogen-associated Molecular Pattern Influence on Clock Gene Expression

From behavior to gene expression, circadian rhythms regulate nearly all aspects of physiology. Here, we present a methodology to challenge mouse splenocytes with the pathogen-associated molecular patterns (PAMPs) lipopolysaccharide (LPS), ODN1826, and heat-killed Listeria monocytogenes and examine their effect on the molecular circadian clock. Previously, studies have focused on examining the influence of LPS on the molecular clock using a variety of in vivo and ex vivo approaches from an assortment of models (e.g., mouse, rat, and human). This protocol describes the isolation and challenge of splenocytes, as well as the methodology to assess clock gene expression post-challenge via quantitative PCR. This approach can be used to assess not only the influence of microbial components on the molecular clock but other molecules as well that may alter expression of the clock. This approach could be utilized to tease apart the molecular mechanism of how PAMP-Toll-like receptor interaction influences clock expression.

This protocol describes a technique using mouse splenocytes to discover pathogen-associated molecular patterns that alter molecular clock gene expression.

From behavior to gene expression, circadian rhythms regulate nearly all aspects of physiology. Here, we present a methodology to challenge mouse ...

Using In Vitro and In-cell SHAPE to Investigate Small Molecule Induced Pre-mRNA Structural Changes

In the process of drug development of RNA-targeting small molecules, elucidating the structural changes upon their interactions with target RNA sequences is desired. We herein provide a detailed in vitro and in-cell selective 2&#39;-hydroxyl acylation analyzed by primer extension (SHAPE) protocol to study the RNA structural change in the presence of an experimental drug for spinal muscular atrophy (SMA), survival of motor neuron (SMN)-C2, and in exon 7 of the pre-mRNA of the SMN2 gene. In in vitro SHAPE, an RNA sequence of 140 nucleotides containing SMN2 exon 7 is transcribed by T7 RNA polymerase, folded in the presence of SMN-C2, and subsequently modified by a mild 2&#39;-OH acylation reagent, 2-methylnicotinic acid imidazolide (NAI). This 2&#39;-OH-NAI adduct is further probed by a 32P-labeled primer extension and resolved by polyacrylamide gel electrophoresis (PAGE). Conversely, 2&#39;-OH acylation in in-cell SHAPE takes place in situ with SMN-C2 bound cellular RNA in living cells. The pre-mRNA sequence of exon 7 in the SMN2 gene, along with SHAPE-induced mutations in the primer extension, was then amplified by PCR and subject to next-generation sequencing. Comparing the two methodologies, in vitro SHAPE is a more cost-effective method and does not require computational power to visualize results. However, the in vitro SHAPE-derived RNA model sometimes deviates from the secondary structure in a cellular context, likely due to the loss of all interactions with RNA-binding proteins. In-cell SHAPE does not need a radioactive material workplace and yields a more accurate RNA secondary structure in the cellular context. Furthermore, in-cell SHAPE is usually applicable for a larger range of RNA sequences (~1,000 nucleotides) by utilizing next-generation sequencing, compared to in vitro SHAPE (~200 nucleotides) that usually relies on PAGE analysis. In case of exon 7 in SMN2 pre-mRNA, the in vitro and in-cell SHAPE derived RNA models are similar to each other.

Detailed protocols for both in vitro and in-cell selective 2&#39;-hydroxyl acylation analyzed by primer extension (SHAPE) experiments to determine the secondary structure of pre-mRNA sequences of interest in the presence of an RNA-targeting small molecule are presented in this article.

In the process of drug development of RNA-targeting small molecules, elucidating the structural changes upon their interactions with target RNA sequences ...

Using Sniper-Cas9 to Minimize Off-target Effects of CRISPR-Cas9 Without the Loss of On-target Activity Via Directed Evolution

The development of clustered regularly interspaced short palindromic repeats (CRISPR)-associated protein 9 (Cas9) into therapeutic modalities requires the avoidance of its potentially deleterious off-target effects. Several methods have been devised to reduce such effects. Here, we present an Escherichia coli-based directed evolution method called Sniper-screen to obtain a Cas9 variant with optimized specificity and retained on-target activity, called Sniper-Cas9. Using Sniper-screen, positive and negative selection can be performed simultaneously. The screen can also be repeated with other single-guide RNA (sgRNA) sequences to enrich for the true positive hits. By using the CMV-PltetO1 dual promoter to express Cas9 variants, the performance of the pooled library can be quickly checked in mammalian cells. Methods to increase the specificity of Sniper-Cas9 are also described. First, the use of truncated sgRNAs has previously been shown to increase Cas9 specificity. Unlike other engineered Cas9s, Sniper-Cas9 retains a wild-type (WT) level of on-target activity when combined with truncated sgRNAs. Second, the delivery of Sniper-Cas9 in a ribonucleoprotein (RNP) format instead of a plasmid format is possible without affecting its on-target activity.

Here, we present a protocol to optimize CRISPR-Cas9 to achieve a higher specificity without the loss of on-target activity. We use a directed evolution approach called Sniper-screen to find a mutant Cas9 with the desired characteristics. Sniper-Cas9 is compatible with truncated single-guide RNAs and delivery in a ribonucleoprotein format, well-known strategies for achieving higher specificities.

The development of clustered regularly interspaced short palindromic repeats (CRISPR)-associated protein 9 (Cas9) into therapeutic modalities requires the ...

A Non-random Mouse Model for Pharmacological Reactivation of Mecp2 on the Inactive X Chromosome

X chromosome inactivation (XCI) is the random silencing of one X chromosome in females to achieve gene dosage balance between the sexes. As a result, all females are heterozygous for X-linked gene expression. One of the key regulators of XCI is Xist, which is essential for the initiation and maintenance of XCI. Previous studies have identified 13 trans acting X chromosome inactivation factors (XCIFs) using a large-scale, loss-of-function genetic screen. Inhibition of XCIFs, such as ACVR1 and PDPK1, using short-hairpin RNA or small molecule inhibitors, reactivates X chromosome-linked genes in cultured cells. But the feasibility and tolerability of reactivating the inactive X chromosome in vivo remains to be determined. Towards this goal, a Xist&#916;:Mecp2/Xist:Mecp2-Gfp mouse model has been generated with non-random XCI due to deletion of Xist on one X chromosome. Using this model, the extent of inactive X reactivation was quantitated in the mouse brain following treatment with XCIF inhibitors. Recently published results show, for the first time, that pharmacological inhibition of XCIFs reactivates Mecp2 from the inactive X chromosome in cortical neurons of the living mouse brain.

Here, we describe a protocol to generate a viable female murine model with non-random X chromosome inactivation, i.e., the maternally-inherited X chromosome is inactive in 100% of the cells. We also describe a protocol to test feasibility, tolerability, and safety of pharmacological reactivation of the inactive X chromosome in vivo.

X chromosome inactivation (XCI) is the random silencing of one X chromosome in females to achieve gene dosage balance between the sexes. As a result, all ...