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    Female fertile phase synchrony, and male mating and reproductive skew, in the crested macaque

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    Biogeography of the cosmopolitan terrestrial diatom Hantzschia amphioxys sensu lato based on molecular and morphological data

    In most of the forest soil samples used in this survey, specimens belonging to the genus Hantzschia are quite common. Based molecular as well as on light microscopy (LM) and scanning electron microscopy (SEM) observations of 25 strains, seven different taxa were recognized. Figure 1 contains the locations of the strain’s habitats. In anticipation of the nomenclatural consequences, we are using the new names already here but will describe them formally later.
    Figure 1

    Map with the habitat locations of the studied strains.

    Full size image

    Molecular data
    The obtained phylogenetic tree for representatives of the different strains Hantzschia contains several large clades, some of which are monophyletic, while others contain several different species names (Fig. 2). In the analyzed tree, the largest clade is represented by different strains of H. amphioxys, the structure of which is described in the corresponding molecular analysis section. At the same time, the most significant is that in the same clade there is strain H. amphioxys D27_008, which has been designated as epitype20. One of the largest is the clade with H. abundans, which, in addition to our strains, and some that have already been published, includes the group of strains referred to as “Hantzschia sp. 3” (Sterre6)e, (Sterre6)f from Souffreau et al.16. We propose to refer to all of these strains as H. abundans. The next clade consists of the new species of H. attractiva and three strains of Hantzschia sp. 2 (Mo1)a, (Mo1)e, (Mo1)m from Souffreau et al.16, the latter we propose to merge into the new species named H. pseudomongolica, which is sister to H. attractiva. Given the topology of the tree and the morphological features of the representatives, we can conclude that there is a close relation between H. abundans and H. attractiva plus H. pseudomongolica. A separate group consists of two clades with sufficient statistical support (likelihood bootstrap, LB 76; posterior probability, PP 100), one of which is represented by two strains of H. parva, and the other with strains of H. cf. amphioxys (Sterre1)f, (Sterre1)h. Another large clade represents a set of strains of Hantzschia sp. 1 and Hantzschia sp. 2 (Mo1)h, (Mo1)l from Souffreau et al.16, among which there are both large cells (86–89 µm length) and smaller ones (37–39 µm length); strains also differ by striation – from 18–20 striae in 10 μm (strain (Mo1)h) to 21–22 in 10 μm (strain (Ban1)h). It is possible that Hantzschia sp. 1 and Hantzschia sp. 2 (Mo1)h, (Mo1)l may be several closely related species. Besides the large clades, there are a number of separate branches in the tree, representing separate strains: Hantzschia sp. 1 (Ban1)d, and the new species H. belgica (H. cf. amphioxys (Sterre3)a from Souffreaua et al.16) and H. stepposa. Interesting is the position of the H. abundans (Tor3)c strain, which is very distant from other representatives of H. abundans and probably is a cryptic taxon, whose taxonomic status needs to be revised.
    Figure 2

    Bayesian tree for representatives of the different strains Hantzschia, from an alignment with 40 sequences and 1785 characters (partial rbcL gene and 28S rDNA fragments). Type strains indicated in bold. The epitype of Hantzschia amphioxys is underlined. Values above the horizontal lines (on the left of slash) are bootstrap support from RAxML analyses ( More

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    Endocranial volume is variable and heritable, but not related to fitness, in a free-ranging primate

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    Investigating an increase in Florida manatee mortalities using a proteomic approach

    This proteomic survey was conducted to identify proteins that were differentially expressed in the serum of manatees affected by two distinct mortality episodes: a red tide group and an unknown mortality episode group in the IRL. These groups were compared to a control group sampled at Crystal River. The red tide group’s exposure was evidenced by the presence of the PbTx antigen, with brevetoxin values in the 4.3 to 14.4 ng/ml range. The other group did not present with clinical symptoms except for mild cold stress in some animals. Two proteomics approaches were employed, 2D-DIGE and shot gun proteomics using LC–MS/MS, which provided similar results, suggesting that several serum proteins were specifically altered in each of the manatee mortality episode groups compared to the Crystal River control group. The differentially expressed serum proteins were cautiously identified based on annotation of the manatee genome6,7 and their amino acid sequence homologies with human serum proteins. While additional work still needs to be done to confirm that the identified manatee proteins function similarly to their human homologs, possible insight on the function of the proteins can be derived from human studies.
    The two proteomics methods used, 2D-DIGE and iTRAQ LC–MS/MS are complementary and both rely on LC–MS/MS for protein identification. 2D-DIGE is a top-down approach, quantifying the differentially expressed proteins at the protein level before identifying the protein by LC–MS/MS, while the iTRAQ method is a bottom-up approach, where the whole proteome is first digested with trypsin, the generated peptides are separated by chromatography and identified and measured by mass spectrometry. Mass spectrometry has become the primary method to analyze proteomes, benefitting from genomic sequences and bioinformatics tools that can translate the sequences into predicted proteins. There are excellent reviews of proteomics methods and how they may be used across species8,9.
    In total, 19 of the 26 proteins identified using the 2D-DIGE method were also identified by iTRAQ (Supplementary Table 1) which showed that these findings were replicated using two complementary experimental methods. In the 2D-DIGE method, most of the proteins were found in multiple spots, suggesting that they were differentially modified. 2D-DIGE can separate proteins based on a single charge difference. Some of the spots contained multiple proteins so it was difficult to determine the fold change of each of the proteins in these spots. For example, protein C4A was identified in 7 different spots, likely representing multiple isoforms. We were not able to corroborate the different post-translational modifications (PTMs) with iTRAQ, as the experiment was not designed to look for PTMs, only total protein quantitation. A drawback of 2D-DIGE is that keratin introduced into the sample from reagents at the time of electrophoresis or through the multiple steps required for protein extraction is also seen in the gels10,11,12. It is unlikely that the keratins were from the serum samples, as blood was collected directly into vacuum tubes. Because of the issue of keratin contamination, the 2D-DIGE method is considered more qualitative in its determination and thus in this study, iTRAQ data were the primary basis for quantitation.
    Pathway analysis detects groups of proteins that are linked in pathways that may be related to disease processes. We used Pathway Studio using subnetwork enrichment analysis to determine disease pathways potentially in place for the red tide and IRL manatees. The Pathway Studio database is constructed from relationships detected between proteins and diseases from articles present in Pubmed but is heavily directed towards human and rodent proteomes. To be able to use this tool, we assigned human homologs to the identified manatee proteins, assuming that based on their sequence homology the proteins would function in a similar way. There are many studies that suggest this assumption has merit, for example Nonaka and Kimura have examined the evolution of the complement system and found clear indications of homology among vertebrates13.
    The top 20 pathways for the red tide group (Table 3) and the IRL group (Table 4) show the diverse set of molecular pathways that may be affected by the exposures. Many of the same pathways appeared for both groups including thrombophilia, inflammation, wounds and injuries, acute phase reaction and amyloidosis. Thrombophilia was the most upregulated pathway for the IRL group (p-value 1.10E-19) and the second most upregulated pathway for the red tide group (p-value 4.1E-19). Thrombophilia, a condition in which blood clots occur in the absence of injury, happens when clotting factors become unbalanced. We obtained proteomics information on 12 of the proteins in this pathway, with some moving in opposing directions. The dysregulated proteins that were increased for both red tide and the IRL groups were SERPIN D1 (Serpin family member D 1), CRP (C-reactive protein), and PLAT (plasminogen activator) and the ones that were decreased in both groups, were SERPIN C1 (Serpin family member C 1), F5 (coagulation factor 5), and ALB (albumin). One protein, AGT (angiotensinogen), was upregulated in the red tide group but downregulated in the IRL. HRG (histidine rich glycoprotein), PROS1 (Protein S), C4BPA (complement component 4 binding protein alpha, and F2 (coagulation factor 2, also known as prothrombin) were downregulated in the red tide group but upregulated in the IRL group. The disparate regulation of proteins in this pathway suggests that clotting was among the pathways disrupted in the affected manatees. Red tide exposed manatees often present with hemorrhagic issues in their intestines, lungs and the brain (14), suggesting that downregulation of coagulation factors may be responsible for this clinical evaluation. Interestingly HRG was upregulated in the IRL by 1.34-fold and downregulated in the red tide group by 0.56-fold, making this protein a good biomarker to distinguish the two events.
    Table 3 Subnetwork enrichment pathways for serum proteins obtained from manatees exposed to red tide.
    Full size table

    Table 4 Subnetwork enrichment pathways for serum proteins obtained from manatees sampled in the IRL.
    Full size table

    Among the manatees in the red tide group, inflammation was ranked 3rd (p-value  More

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