Convergent synaptic and circuit substrates underlying autism genetic risks

Aaron MCGEE , Guohui LI , Zhongming LU , Shenfeng QIU

Front. Biol. ›› 2014, Vol. 9 ›› Issue (2) : 137 -150.

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Front. Biol. ›› 2014, Vol. 9 ›› Issue (2) : 137 -150. DOI: 10.1007/s11515-014-1298-y
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Convergent synaptic and circuit substrates underlying autism genetic risks

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Abstract

There has been a surge of diagnosis of autism spectrum disorders (ASD) over the past decade. While large, high powered genome screening studies of children with ASD have identified numerous genetic risk factors, research efforts to understanding how each of these risk factors contributes to the development autism has met with limited success. Revealing the mechanisms by which these genetic risk factors affect brain development and predispose a child to autism requires mechanistic understanding of the neurobiological changes underlying this devastating group of developmental disorders at multifaceted molecular, cellular and system levels. It has been increasingly clear that the normal trajectory of neurodevelopment is compromised in autism, in multiple domains as much as aberrant neuronal production, growth, functional maturation, patterned connectivity, and balanced excitation and inhibition of brain networks. Many autism risk factors identified in humans have been now reconstituted in experimental mouse models to allow mechanistic interrogation of the biological role of the risk gene. Studies utilizing these mouse models have revealed that underlying the enormous heterogeneity of perturbed cellular events, mechanisms directing synaptic and circuit assembly may provide a unifying explanation for the pathophysiological changes and behavioral endophenotypes seen in autism, although synaptic perturbations are far from being the only alterations relevant for ASD. In this review, we discuss synaptic and circuit abnormalities obtained from several prevalent mouse models, particularly those reflecting syndromic forms of ASD that are caused by single gene perturbations. These compiled results reveal that ASD risk genes contribute to proper signaling of the developing gene networks that maintain synaptic and circuit homeostasis, which is fundamental to normal brain development.

Keywords

autism spectrum disorders / development / risk genes / synapse / circuits / behavior / neurodevelopmental disorders

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Aaron MCGEE, Guohui LI, Zhongming LU, Shenfeng QIU. Convergent synaptic and circuit substrates underlying autism genetic risks. Front. Biol., 2014, 9(2): 137-150 DOI:10.1007/s11515-014-1298-y

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Introduction

Tsunamis are sea surface gravity waves generated by large-scale underwater disturbances. Typical trigger mechanisms are earthquake initiated seabed displacements, volcanic eruptions, landslides (including underwater landslides), impact of large objects (such as meteors) falling into the open ocean and underwater explosions. These waves are known to be able to cause significant alterations in the coastal systems (Dawson, 1994; Bryant et al., 1996; Bryant, 2001; Scheffers and Kelletat, 2003). They may produce extensive changes in coastline topography, considerable erosion and subsequent deposition of substantial quantity of sediments in a short span. The December 2004 Asian earthquake and the subsequent tsunami off the east coast of Sumatra in Indonesian Archipelago have affected most of the countries around the Indian Ocean. The tsunami deposits in the land along the south-east coast of India have signatures of different geological features, which inundated to deeper regions (Nagendra et al., 2005; Srinivasalu et al., 2007, 2008). Many studies are available on ancient and recent tsunami deposits, including the descriptions of tsunami deposits in coastal lake, estuary, lagoon, bay floor, shelf and deep sea tsunami deposit environments (Konno, 1961; Bourgeois et al., 1988; Yamazaki et al., 1989; Cita and Aloisi, 2000). In general, disastrous tsunamis change the biodiversity of marine ecosystems, because the tsunami waves travel thousands of kilometers in the sea, with a lot of washed out materials from the land. One of the most significant phenomena related to tsunami inundations is large-scale sediment removal from the coast, followed by widespread deposition of marine sand on coastal lowlands (Minoura and Nakaya, 1991). So there will be a possibility of demineralization in the marine environment. The impact of tsunami spreading their traces not only to the life of marine benthos and also it affects the diversity of marine microbes (Altaff et al., 2005).

Historical evidences revealed that, only two earth quakes (1881 and 1941) have made a mysterious tsunami effect in the east coast of India (Rajendran et al., 2005). The marine ecosystem is affected by physical disturbances like tsunami, hurricanes and storms etc. which affect the benthos by changing the sediment characteristics and available food resources (Boesch et al., 1976a; Van Blaricom, 1982; Thistle et al., 1995). Several researchers have undertaken studies related to the impact of tsunami on microbial population in south-east coast of India (Subramani et al., 2006; Ramesh et al., 2006; Mahalakshmi et al., 2011; Surajit Das et al., 2013). When giant tidal waves like the tsunami occur in the sea, it is possible that the deeper nutrient rich water comes up to the surface (Levinton, 2001). This might have influenced the marine environment to a great extent because of nutrient and mineral flux resulting in variation in marine biodiversity in pre- and post-tsunami sediments. This has prompted to assess the microbial diversity in pre- and post-tsunami sediments in the study area. Microorganisms also have an important and established biogeochemical role within intertidal ecosystems, carrying out crucial transformations and remineralization of organic matter (Decho et al., 2005). Most of the microbes like Vibrios, Halomonas, Pseudomonas sp. and E. coli are pathogenic to human health and some lead to fatal infectious (Carlson et al., 1968; Grimes, 1975; Gerba and Schaiberger, 1975; Blacke et al., 1981). The diversity, occurrence and activity of heterotrophic bacteria are controlled by several hydro biological factors and nutrient levels present in the aquatic environment and have been well established in marine ecosystem (Azam et al., 1983; Ducklow and Hill, 1985). The environmental constraints like high temperature, exposed to UV (ultra violet) radiation, drought, pysico-chemical alterations with intense marine biological interactions create a competition for food and space to the microbial population (Lindow and Brandl, 2003). The population density of Vibrio sp. in the marine environment is usually high because it can withstand a wide range of aquatic environments including estuaries and marine sediments (Urakawa et al., 2000; Thompson et al., 2004). Microorganisms spreading in the marine and brackish ecosystem play an important role in the decomposition of organic nutrients and enhance mineralization (Hollibaugh et al., 1980). Hence there has been an endeavor to evaluate the impact of tsunami on microbial diversity.

Study area

The study area extends to about 35 km between Vanagiri and Nagoor (11°08′47.1″ to 10°48′80.7″ N and 79°51′42.6″ to 79°51′05.8″ E) in the south-east coast of India (Table 1). It is located north of Point Calimere region at the southern tip of the Bay of Bengal. The rivers Uppanar, Vellar, Gadilum and Cauvery pass through the granitic terrain and agricultural belt in Tamil Nadu State before draining into the Bay of Bengal. The coastal stretch is affected by the seasonal monsoon (every year) in the latter half of the year (October–December) (Sarma et al., 1990). The study area is normally shallow, with the depth varying from 5 to 30 m for nearly 80 km2 parallel to the coast and the shallow nature extends into the Palk Strait region in the southern side (Stephen-Pichaimani et al., 2008). The geology around the study area indicates different types of rocks which include alluvium, charnockite, khondalite, garnet-sillimanaite gneiss, pink/gray granite, amphibolites, pyroxenites and biotite schists, which lie in the southern part of the study area (Vasudevan and Seetaramaswamy, 1983). In addition, the southern part of Cauvery basin (part of Nagapattinam and Karikal Town) in the peninsular shield is underlain by rocks of Archean age and the coastal tract is covered by younger alluvium and coastal sands (Mohanachandran and Subramanian, 1990). The study area also witnessed maximum backwash of sediments from land during/after the three major tsunami waves that struck the coastal region (Srinivasalu et al., 2009).

Materials and methods

Intertidal Marine sediments (0–15 cm) were collected from 12 sampling locations along the south-east coast of India during pre- and post-tsunami periods. The sediments were collected using a handy sampler in sterile polypropylene bags and transferred to laboratory for further analysis. The wet marine sediments were sub-sampled for isolation of cultured bacteria and fungi. A serial dilution was performed by adding 1 g of soil to 99 ml of sterile distilled water and diluted serially to 10-6. The plates were incubated at room temperature up to 48 h in the case of bacteria and 5 days for fungi. The microbial diversity was counted and expressed as colony forming units (CFUs) per gram of sediments. Individual colonies were picked up and subcultured in the respective medium, and the colony characteristics such as size, shape, pigmentation and exopolysaccharide (EPS) production, etc. were recorded. The bacteria isolated from pre- and post-tsunami sediments were categorized on the basis of Gram’s reaction. All the isolated bacteria were streaked on Eosin Methylene Blue agar selective medium to determine the Coliforms (Vieira et al., 2001) and Zobell marine agar medium is used to culture other halophilic bacteria. The same Rose Bengal media can be used as its composition encourages the fungal diversity. Vibrio species were determined in Thiosulfate Citrate Bile-salt Sucrose agar and further confirmed by their shape through microscopic investigation (Arias et al., 1998). Bacterial diversity was determined by Paul and Clark (1998) method.
CFUs were calculated by the following formula
CFUs/mL=Number of colonies/dilution×amount plated

Results

The present investigation highlights the ubiquitous distribution of bacterial diversity in the marine sediments during the pre- and post-tsunami periods, along the south-east coast of India. Based on the colony morphology, 26 strains were selected and sub cultured, and 5 generas were identified viz. Vibrio, Halomonos, Serratia, Pseudomonas and Escherichia. Among these, Vibrio constituted 33.3% followed by Serratia (28.7%), Escherichia coli (14.3%), Pseudomonas (12.9%) and Halomonos (10.6%). All the isolated bacterial species belonged to the gram negative group. In the case of pathogenic bacteria, a total of 3 species (Vibrio Parahemolyticus, Pseudomonas aeruginosa and Escherichia coli) were recorded (Fig. 1).

The occurrence of more number of pathogenic species (bacteria and fungus) in the pre tsunami sediments of the study area maybe due to the confluence of rivers with urban runoff. The population of microbes and fungi species are drastically reduced and some of the pathogenic microbes are noticed after backwashing effect of the tsunami inundation. This may be due to the withstanding behaviour of such pathogens. They can survive beyond the extreme condition i.e tsunami effect.

Population density of bacterial species during pre- and post-tsunami periods in the coastal sediments varied from 14 × 106 to 25 × 106 CFU/g and 4 × 106 to 9 × 106 CFU/g. In general, higher bacterial diversity is due to rich organic matters and high residence time of the microorganisms in the sediments. The bacterial diversity is drastically reduced in tsunamigenic sediments except pathogenic species (Fig. 2). According to Surjit Das et al. (2005) the higher diversity of pathogenic bacteria species along the coast after the tsunami is most probably due to inundated tsunami water. The mean population density of pathogenic bacteria species during pre and post tsunami periods ranges from 4.0 × 106 to 7.4 × 106 CFU/g. Halophilic Vibrios can represent as much as 40% of the total microbiota of the subtropical coastal waters (Cheung et al., 1990). The considerable population density of Vibrio spp. (31.5%) in the pre- and post-tsunami, marine environment suggests that they survive in a wide range of aquatic environments including estuaries, marine, coastal waters and sediments. The low diversity of Escherichia coli in the study area indicates less pollution in the coastal sediments. Among the pathogenic species, no Pseudomonas aeruginosa diversity was recorded and a considerable population density of Escherichia coli and Vibrio parahemolyticus (25 × 106 CFU/g) was retained after the tsunami. The decrease of other bacterial diversity in the sediments after the tsunami is attributed to the demineralization of organic matter from the coastal and shelf sediments which support the growth of microbes. The continuous exchange of ocean water and backwashing of coastal sediments during the tsunami wave or the tidal wave or the tidal oscillation in the full moon and newmoon period might have reduced the pathogenic bacterial diversity in the sediments.

Fungal species such as Penecillium, Aspergillus and Fusarium were recorded in the study area (Fig. 4). Population densities of fungal species like Penecillium and Aspergillus were more in post tsunami sediments when compared to pre tsunami sediments (37.9% to 49.7% and 26.13% to 43.5%) (Fig. 3). It was also observed that Fusarium sps. in the post tsunami sediments were considerably decreased from 35.8 to 20.4%.

Pearson correlation matrix (PCM)

Pearson correlation matrix was used to determine the relationship among the sediment, nutrients with the physico-chemical properties and microbial diversity of the marine sediments and to estimate the relation between the variables. Correlation matrix was calculated among all the four variables for different locations in both pre- and post-tsunami sediments and a comprehensive chart is prepared in Table 2 A and 2B.

A good correlation has been observed between amino acid and carbohydrate in pre-tsunami. However, after tsunami the correlation grows negatively. It shows slightly inversely proportional between these two parameters. Moreover, a negative correlation (r = -0.509) has observed between bacteria and carbohydrate in post-tsunami period. However, it is noticed that there is no relationship between bacteria and carbohydrate in both the periods, as well as in pre-tsunami amino acid and bacteria has inversely correlated (r = -0.223). But an interesting positive correlation is observed between fungus and carbohydrate in both pre-and post-tsunami (r = 0.777** and r = 0.630*).

Principal component analysis (PCA)

The evaluation of sediment nutrients (carbohydrate, amino acid) and microbial diversity (bacteria and fungus) relationship within the study area and the source identification, principal component analysis was used following standard procedure reported in literature (Jolliffe, 1986; Rubio et al., 2000; Yu et al., 2008; Dragović et al., 2008). PCA formed on the logarithmic form of the data variables. The results of the PCA for pre- and post-tsunami sediment samples are shown in Table 3 A and B. Three principal components (PCs) were extracted. Therefore, these three factors play a significant role in the microbial diversity in the study area. PCA was carried out using the PRIMER v6 software package (Plymouth Routines In Multivariate Ecological Research).

The Table 3 A and 3B illustrates that PC1 indicative of carbohydrate concomitant with amino acid and fungus. It may be due to the mixing of organic nutrients through riverine process. PC2 positively associated with bacteria. PC3 indicates a positive relationship with fungal diversity. The PCA showed that carbohydrate, amino acid and fungal diversity are strongly correlated in PC1. Bacterial diversity was remarkably dominant in PC2. In PC1 Bacterial diversity had a negative correlation to the other variables. In PC2 bacterial diversity had a positive correlation and carbohydrate and amino acid variables are also correlated with the PC2. But fungal diversity had a negative correlation to the other variables. In PC3 indicates a positive correlation in fungus and bacteria but the rest of them are negatively correlated.

Conclusion

The screening of tsunami sediments reveals that marine fungi and pathogenic microbial density are abundant in post tsunami sediments. The overall analysis indicates that the increase of pathogenic bacterial and fungal diversity in the post tsunami period is most probably due to inundation and the backwashing effect of the tsunami waves along the study area. The decrease in other bacterial diversity in the post tsunami sediments is most probably due to the demineralization of organic matter and continuous exchange of ocean water and backwashing of coastal sediments and it might be the retaining ability of the marine microbes in the intertidal ecosystem.

References

[1]

AltaffK, SugumaranJ M, NaveedS (2005). Impact of tsunami on meiofauna of Marina beach, Chennai, India. Current Sci, 89(10): 1646

[2]

AriasC R, AznarR, PujalteM J, GarayE (1998). A comparison of strategies for the detection and recovery of Vibrio vulnificus from marine samples of the western Mediterranean coast. Syst Appl Microbiol, 21(1): 128–134

[3]

AzamF, FenchelT, FieldJ G, GrayJ S, Meyer-ReilL A, ThingstadF (1983). The ecological role of water- column microbes in the sea. Mar Ecol Prog Ser, 10: 257–263

[4]

BlackeP A, WeanerR E, HoillisD G (1981). Diseases of humans (other than cholera) caused by Vibrio. Annu Rev Microbiol, 34(1): 341–347

[5]

BoeschD F, DiazR J, VirnsteinR W (1976a). Effects of tropical storm Agnes on soft-bottom communities of the James and York estuaries and the lower Chesapeake Bay. Chesap Sci, 17(4): 246–259

[6]

BourgeoisJ, HansenT A, WibergP L, KaufmannE G (1988). A tsunami deposit at the Cretaceous-Tertiary Boundary in Texas. Science241:567–570

[7]

BryantE (2001). Tsunami. The underrated hazard. Cambridge University Press, Cambridge

[8]

BryantE, YoungR, PriceD (1996). Tsunami as a major control of coastal evolution, southeastern Australia. J Coast Res, 12: 831–840

[9]

CarlsonG F, WoodardF E, WentworthD F, SproulO J (1968). Virus inactivation on clay particles in natural waters, Journal of the Water Pollution Control Federation. 40:98–106

[10]

CheungW H S, ChangK C K, HungR P S, KleevensJ W L (1990). Health effects of beach water pollution in Hong Kong. Epidemiol Infect, 105(1): 139–162

[11]

CitaM B, AloisiG (2000). Deep-sea tsunami deposits triggered by the explosion of Santorini (3500 y BP), eastern Mediterranean. Sediment Geol, 135(1–4): 181–203

[12]

DasS, LylaP S, Ajmal KhanS (2013). The distribution and diversity of culturable aerobic heterotrophic benthic bacteria in the continental slope of the Bay of Bengal: Linked abiotic factors, including a tsunami. Russ J Mar Biol, 39(3): 169–181

[13]

DawsonA G (1994). Geomorphological effects of tsunami run-up and backwash.Geomorphology, 10(1–4): 83–94

[14]

DechoA W, VisscherP T, ReidR P (2005). Production and cycling of natural microbial exopolymers (EPS) within a marine stromatolite. Palaeogeogr Palaeoclimatol Palaeoecol, 219(1–2): 71–86

[15]

DragovićS, MihailovićN, GajićB (2008). Heavy metals in soils: distribution, relationship with soil characteristics and radionuclides and multivariate assessment of contamination sources. Chemosphere, 72(3): 491–495

[16]

DucklowH W, HillS M (1985). Tritiated thymidine incorporation and the growth of heterotrophic bacteria in warm core rings’. Limnol Oceanogr, 30(2): 260–272

[17]

GerbaC P, SchaibergerG E (1975). Effect of particulates on virus survival in seawater. J Water Pollut Control Fed, 47(1): 93–103

[18]

GrimesD J (1975). Release of sediment-bound fecal coliforms by dredging. Appl Microbiol, 29(1): 109–111

[19]

HollibaughJ T, CarruthersA B, FuhrmanJ A, AzamF (1980). Cycling of organic nitrogen inmarine plankton communities studied in enclosed water columns. Mar Biol, 59(1): 15–21

[20]

JolliffeI T (1986). Principal Component Analysis, Springer, New York.

[21]

KonnoE (1961). Geological observations of the Sanriku coastal region damaged by the tsunami due to the Chile earthquake in 1960. Contributions to the Institute of Geology and Paleontology. Tohoku University, 52: 1–40

[22]

LevintonJ S (2001). Marine Biology Function, Biodiversity and Ecology, 2nd ed. New York: Oxford University Press,PP. 515

[23]

LiY, GouX, WangG, ZhangQ, SuQ, XiaoG (2008). Heavy metal contamination and source in arid agricultural soil in central Gansu Province, China. J Environ Sci (China), 20(5): 607–612

[24]

LindowS E, BrandlM T (2003). Microbiology of the phyllosphere. Appl Environ Microbiol, 69(4): 1875–1883

[25]

MahalakshmiM, SrinivasanM, MuruganM, balakrishnanS, DevanathanK (2011). Isolation and identification of total Heterotrophic Bacteria and human pathogens in water and sediment from cuddalore fishing harbour after the tsunami. Asian J Biol Sci, 4: 148–156

[26]

MinouraK, NakayaS (1991). Traces of tsunami preserved in intertidal lacustrine and marsh deposits: some examples from northeast Japan. J Geol, 99(2): 265–287

[27]

MohanachandranG, SubramanianV (1990). Texture, mineralogy and elemental composition of sediments along the southeast coast of India. Indian J Mar Sci, 19: 128–132

[28]

NagendraR, KamalakannanB V, SajithC, SenG, ReddyA N, SrinivasaluS (2005). A record of foraminiferal assemblage in tsunami sediments along Nagappattinam Coast, Tamil Nadu. Curr Sci, 89(11): 1947–1952

[29]

PaulE A, ClarkF E (1998). Soil microbiology and biochemistry. NewYork: Academic.press: 2nd Edition

[30]

RajendranK, RajendranC P, Anil Earnest (2005). The great Sumathra Andaman earthquake of 26 December 2004. Curr Sci, 88(1): 11–12

[31]

RameshS, JayaprakashvelM, MathivananN (2006). Microbial status in seawater and coastal sediments during pre- and post-tsunami periods in the Bay of Bengal, India. Mar Ecol (Berl), 27(3): 198–203

[32]

RubioB, NombelaM A, VilasF (2000). Geochemistry of major and trace elements in sediments of the Ria de Vigo (NW Spain): an assessment of metal pollution. Mar Pollut Bull, 11(11): 968–980

[33]

SarmaV V B, MurtyV S N, RaoD P (1990). Distribution of cyclone heat potential in the Bay of Bengal. Indian J Mar Sci, 19: 102–106

[34]

ScheffersA, KelletatD (2003). Sedimentologic and geomorphologic tsunami imprints worldwide—a review. Earth Sci Rev, 63(1–2): 83–92

[35]

SrinivasaluS, Rajeshwara-RaoN, ThangaduraiN, JonathanM P, RoyP D, Ram-MohanV, SaravananP (2009) Characteristics of 2004 tsunami deposits of northern Tamil Nadu coast, India. Boletındela Sociedad Geolo’gica Mexicana

[36]

SrinivasaluS, ThangaduraiN, JonathanM P, Armstrong-AltrinJ S, AyyamperumalT, Ram MohanV (2008). Evaluation of trace metal enrichments from the 26 December 2004 tsunami sediments along southeast coast of India. Env Geol, 53(8): 1711–1721

[37]

SrinivasaluS, ThangaduraiN, SwitzerA D, Ram MohanV, AyyamperumalT (2007). Erosion and sedimentation in Kalpakkam (N Tamil Nadu, India) from the 26th December 2004 M9 tsunami.Mar Geol, 240(1–4): 65–75

[38]

Stephen-PichaimaniV, JonathanM P, SrinivasaluS, Rajeshwara-RaoN R, MohanS P (2008). Enrichment of trace metals in surface sediments from northern part of Point Calimere, SE coast of India. Env Geol, 55(8): 1811–1819

[39]

SubramaniR, ManiJ, NarayanasamyM (2006). Microbial status in sea water and coastal sediments during pre and post-tsunami periods in the Bay of Bengal, India. Marine Ecology, 27(3): 198–203

[40]

Surjit DasP S, Lyla, Ajmal KhanS (2005). Variation in microbial diversity in a Mangrove Ecosystem in Parangipettai coast (Southeast coast of India): Effect of Tsunami? Res. J. Chem Environ, 9: 46–49

[41]

ThistleD, WeatherlyG L, ErtmanS C (1995). Shelf harpacticoid copepods do not escape into the seabed during winter storms. J Mar Res, 53(5): 847–863

[42]

ThompsonF L, IidaT, SwingsJ (2004). Biodiversity of vibrios. Microbiol Mol Biol Rev, 68(3): 403–431

[43]

UrakawaH, YoshidaT, NishimuraM, OhwadaK (2000). Characterization of depth-related population variation in microbial communities of a coastal marine sediment using 16S rDNA-based approaches and quinone profiling. Environ Microbiol, 2(5): 542–554

[44]

Van BlaricomG R (1982). Experimental analysis of structural regulation in a marine sand community exposed to oceanic swell. Ecol Monogr, 52(3): 283–305

[45]

VasudevanV, SeetaramaswamyA (1983). Distribution of clay minerals in modern sediments of Palk Bay. Indian J Mar Sci, 12: 218–219

[46]

VieiraR H S F, RodriguesD P, MenezesE A, EvangelistaN S S, RiesE M F R, BarretoL M (2001). Microbial contamination of sand from major beaches in Fortaleza, Ceará state, Brazil. Braz J Microbiol, 32(2): 77–80

[47]

YamazakiT, YamaokaM, ShikiT (1989). Miocene offshore tractive current-worked conglomerates- Tsubutegaura, Chiba Peninsula, central Japan. Sediment Geol, 135: 231–239

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