How Should Research And Monitoring Be Integrated?

Scientific knowledge of Chesapeake Bay and tidal tributaries has accumulated over many years beginning mostly with descriptive surveys prior to the 1960\u27s and 1970\u27s and evolving towards a coupling of monitoring and research in recent years. This essay discusses the need to more fully couple monitoring and research efforts in the Bay system because such a union of efforts is argued to be the most effective way to assess gross trends in the health of the system (monitoring) and to understand the basic forces causing these trends (research). We argue that together they provide part of the framework necessary for effective management of the living resources of the bay region.https://scholarworks.wm.edu/vimsbooks/1176/thumbnail.jp

Tumour-associated and non-tumour-associated microbiota in colorectal cancer

Objective: A signature that unifies the colorectal cancer (CRC) microbiota across multiple studies has not been identified. In addition to methodological variance, heterogeneity may be caused by both microbial and host response differences, which was addressed in this study. Design: We prospectively studied the colonic microbiota and the expression of specific host response genes using faecal and mucosal samples (‘ON’ and ‘OFF’ the tumour, proximal and distal) from 59 patients undergoing surgery for CRC, 21 individuals with polyps and 56 healthy controls. Microbiota composition was determined by 16S rRNA amplicon sequencing; expression of host genes involved in CRC progression and immune response was quantified by real-time quantitative PCR. Results: The microbiota of patients with CRC differed from that of controls, but alterations were not restricted to the cancerous tissue. Differences between distal and proximal cancers were detected and faecal microbiota only partially reflected mucosal microbiota in CRC. Patients with CRC can be stratified based on higher level structures of mucosal-associated bacterial co-abundance groups (CAGs) that resemble the previously formulated concept of enterotypes. Of these, Bacteroidetes Cluster 1 and Firmicutes Cluster 1 were in decreased abundance in CRC mucosa, whereas Bacteroidetes Cluster 2, Firmicutes Cluster 2, Pathogen Cluster and Prevotella Cluster showed increased abundance in CRC mucosa. CRC-associated CAGs were differentially correlated with the expression of host immunoinflammatory response genes. Conclusions: CRC-associated microbiota profiles differ from those in healthy subjects and are linked with distinct mucosal gene-expression profiles. Compositional alterations in the microbiota are not restricted to cancerous tissue and differ between distal and proximal cancers

The oral microbiota in colorectal cancer is distinctive and predictive

Background and aims: Microbiota alterations are linked with colorectal cancer (CRC) and notably higher abundance of putative oral bacteria on colonic tumours. However, it is not known if colonic mucosa-associated taxa are indeed orally derived, if such cases are a distinct subset of patients or if the oral microbiome is generally suitable for screening for CRC. Methods: We profiled the microbiota in oral swabs, colonic mucosae and stool from individuals with CRC (99 subjects), colorectal polyps (32) or controls (103). Results: Several oral taxa were differentially abundant in CRC compared with controls, for example, Streptococcus and Prevotellas pp. A classification model of oral swab microbiota distinguished individuals with CRC or polyps from controls (sensitivity: 53% (CRC)/67% (polyps); specificity: 96%). Combining the data from faecal microbiota and oral swab microbiota increased the sensitivity of this model to 76% (CRC)/88% (polyps). We detected similar bacterial networks in colonic microbiota and oral microbiota datasets comprising putative oral biofilm forming bacteria. While these taxa were more abundant in CRC, core networks between pathogenic, CRC-associated oral bacteria such as Peptostreptococcus, Parvimonas and Fusobacterium were also detected in healthy controls. High abundance of Lachnospiraceae was negatively associated with the colonisation of colonic tissue with oral-like bacterial networks suggesting a protective role for certain microbiota types against CRC, possibly by conferring colonisation resistance to CRC-associated oral taxa and possibly mediated through habitual diet. Conclusion: The heterogeneity of CRC may relate to microbiota types that either predispose or provide resistance to the disease, and profiling the oral microbiome may offer an alternative screen for detecting CRC

Combination treatment with Grb7 peptide and Doxorubicin or Trastuzumab (Herceptin) results in cooperative cell growth inhibition in breast cancer cells

Grb7 has potential importance in the progression of cancer. We have previously identified a novel peptide that binds to the SH2 domain of Grb7 and inhibits its association with several different receptor tyrosine kinases. We have synthesised the Grb7 peptide, G7-18NATE, with two different cell penetrating peptides, Penetratin and Tat. In this study, we have shown that both Penetratin- and Tat-conjugated G7-18NATE peptides are able to inhibit the proliferation of SK-BR-3, ZR-75-30, MDA-MB-361 and MDA-MB-231 breast cancer cells. There was no significant effects on breast cancer MCF-7cells, non-malignant MCF 10A or 3T3 cells. In addition, there was no significant inhibition of proliferation by Penetratin or Tat alone or by their conjugates with arbitrary peptide sequence in any of the cell lines tested. We determined the EC50 of G7-18NATE-P peptide for SK-BR-3 cell proliferation to be 7.663 × 10−6 M. Co-treatment of G7-18NATE-P peptide plus Doxorubicin in SK-BR-3 breast cancer cells resulted in an additional inhibition of proliferation, resulting in 56 and 84% decreases in the Doxorubicin EC50 value in the presence of 5 × 10−6 and 1.0 × 10−5 M G7-18NATE-P peptide, respectively. Importantly, the co-treatment with Doxorubicin and the delivery peptide did not change the Doxorubicin EC50. Since Grb7 associates with ErbB2, we assessed whether the peptide inhibitor would have a combined effect with a molecule that targets ErbB2, Herceptin. Co-treatment of Herceptin plus 1.0 × 10−5 M G7-18NATE-P peptide in SK-BR-3 cells resulted in a 46% decrease in the Herceptin EC50 value and no decrease following the co-treatment with Herceptin and penetratin alone. This Grb7 peptide has potential to be developed as a therapeutic agent alone, in combination with traditional chemotherapy, or in combination with other targeting molecules

Evidence of a Putative Deep Sea Specific Microbiome in Marine Sponges

The microbiota of four individual deep water sponges, Lissodendoryx diversichela, Poecillastra compressa, Inflatella pellicula, and Stelletta normani, together with surrounding seawater were analysed by pyrosequencing of a region of the 16S rRNA gene common to Bacteria and Archaea. Due to sampling constraints at depths below 700 m duplicate samples were not collected. The microbial communities of L. diversichela, P. compressa and I. pellicula were typical of low microbial abundance (LMA) sponges while S. normani had a community more typical of high microbial abundance (HMA) sponges. Analysis of the deep sea sponge microbiota revealed that the three LMA-like sponges shared a set of abundant OTUs that were distinct from those associated with sponges from shallow waters. Comparison of the pyrosequencing data with that from shallow water sponges revealed that the microbial communities of all sponges analysed have similar archaeal populations but that the bacterial populations of the deep sea sponges were distinct. Further analysis of the common and abundant OTUs from the three LMA-like sponges placed them within the groups of ammonia oxidising Archaea (Thaumarchaeota) and sulphur oxidising ?-Proteobacteria (Chromatiales). Reads from these two groups made up over 70% of all 16S rRNA genes detected from the three LMA-like sponge samples, providing evidence of a putative common microbial assemblage associated with deep sea LMA sponges

Fecal microbiota variation across the lifespan of the healthy laboratory rat.

Laboratory rats are commonly used in life science research as a model for human biology and disease, but the composition and development of their gut microbiota during life is poorly understood. We determined the fecal microbiota composition of healthy Sprague Dawley laboratory rats from 3 weeks to 2 y of age, kept under controlled environmental and dietary conditions. Additionally, we determined fecal short-chain fatty acid profiles, and we compared the rat fecal microbiota with that of mice and humans. Gut microbiota and to a lesser extent SCFAs profiles separated rats into 3 different clusters according to age: before weaning, first year of life (12- to 26-week-old animals) and second year of life (52- to 104-week-old). A core of 46 bacterial species was present in all rats but its members' relative abundance progressively decreased with age. This was accompanied by an increase of microbiota α-diversity, likely due to the acquisition of environmental microorganisms during the lifespan. Contrastingly, the functional profile of the microbiota across animal species became more similar upon aging. Lastly, the microbiota of rats and mice were most similar to each other but at the same time the microbiota profile of rats was more similar to that of humans than was the microbiota profile of mice. These data offer an explanation as to why germ-free rats are more efficient recipients and retainers of human microbiota than mice. Furthermore, experimental design should take into account dynamic changes in the microbiota of model animals considering that their changing gut microbiota interacts with their physiology.NG received a PhD scholar grant from the French “Ministère de l'Enseignement et de la Recherche”. WT received a PhD scholar grant from the Auvergne council. PPC received a post-doctoral fellowship from “Université d'Auvergne”. Work in PWOT's laboratory was supported by Science Foundation Ireland through a Centre award to the APC Microbiome Institute (SFI/12/RC/2273)