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Population Analysis of Subsaturated 172-12 Nucleosomal Arrays by Atomic Force Microscopy Detects Nonrandom Behavior That Is Favored by Histone Acetylation and Short Repeat Length

2001; Elsevier BV; Volume: 276; Issue: 51 Linguagem: Inglês

10.1074/jbc.m104916200

1083-351X

R. Bash, Jaya G. Yodh, Yuri L. Lyubchenko, Neal W. Woodbury, D. Lohr,

Advanced biosensing and bioanalysis techniques

Concatameric 5 S rDNA templates reconstitutedin vitro into nucleosomal arrays provide very popular chromatin models for many kinds of studies. Here, atomic force microscopy is used to determine the population distributions for one such nucleosomal array, the 172-12, reconstituted to various subsaturated levels with nonacetylated or hyperacetylated HeLa histones. This array is a model for short linker length genomes and transcriptionally active and newly replicated chromatins. The analysis shows that as input histone levels increase, template occupation increases progressively as discrete population distributions. The distributions are random at low (n av < 4) and high (n av > 8) loadings but display specific nonrandom features, such as a deficit of molecules with one nucleosome more or less than the peak species in the distribution and enhanced distribution breadths, in the mid-range (n av = 4–8). Thus, the mid-range of occupation on polynucleosomal arrays may be a special range for chromatin structure and/or assembly. The mid-range nonrandom features are enhanced in distributions from short repeat (172-12) arrays, particularly for unacetylated chromatin, and in distributions from hyperacetylated chromatin, particularly for long repeat (208-12) arrays. Thus, short repeat length and acetylation can affect basic chromatin properties, like population tendencies, in very similar ways and therefore may cause similar changes in chromatin structure. Some possible effects are suggested. The data also indicate that it is thermodynamically more difficult for hyperacetylated nucleosomes to assemble onto the 172-12 templates, a result having implications for in vivo chromatin assembly. Concatameric 5 S rDNA templates reconstitutedin vitro into nucleosomal arrays provide very popular chromatin models for many kinds of studies. Here, atomic force microscopy is used to determine the population distributions for one such nucleosomal array, the 172-12, reconstituted to various subsaturated levels with nonacetylated or hyperacetylated HeLa histones. This array is a model for short linker length genomes and transcriptionally active and newly replicated chromatins. The analysis shows that as input histone levels increase, template occupation increases progressively as discrete population distributions. The distributions are random at low (n av < 4) and high (n av > 8) loadings but display specific nonrandom features, such as a deficit of molecules with one nucleosome more or less than the peak species in the distribution and enhanced distribution breadths, in the mid-range (n av = 4–8). Thus, the mid-range of occupation on polynucleosomal arrays may be a special range for chromatin structure and/or assembly. The mid-range nonrandom features are enhanced in distributions from short repeat (172-12) arrays, particularly for unacetylated chromatin, and in distributions from hyperacetylated chromatin, particularly for long repeat (208-12) arrays. Thus, short repeat length and acetylation can affect basic chromatin properties, like population tendencies, in very similar ways and therefore may cause similar changes in chromatin structure. Some possible effects are suggested. The data also indicate that it is thermodynamically more difficult for hyperacetylated nucleosomes to assemble onto the 172-12 templates, a result having implications for in vivo chromatin assembly. base pair(s) atomic force microscopy A characteristic feature of eukaryotic chromatins is their significant variability in average nucleosome repeat length, a feature that arises from variations in the average lengths of linker DNA that separate the conserved core nucleosomal particles in vivo (1Compton J.L. Bellard M. Chambon P. Proc. Natl. Acad. Sci. U. S. A. 1976; 73: 4382-4386Crossref PubMed Scopus (184) Google Scholar, 2Lohr D. Corden J. Kovacic T. Tatchell K. van Holde K.E. Proc. Natl. Acad. Sci. U. S. A. 1977; 74: 79-83Crossref PubMed Scopus (123) Google Scholar). Average genomic repeat lengths range from ∼156 to ∼250 bp1 (3Van Holde K. Chromatin. Springer-Verlag New York Inc., New York1988Google Scholar, 4Widom J. Annu. Rev. Biophys. Biomol. Struct. 1998; 27: 285-327Crossref PubMed Scopus (250) Google Scholar), but there are some trends. For example, in transcriptionally activeSaccharomyces cerevisiae, the average nucleosome repeat is ∼170 bp, whereas in the inactive, terminally differentiated chicken erythrocyte, it is 208 bp (3Van Holde K. Chromatin. Springer-Verlag New York Inc., New York1988Google Scholar). The indication that transcriptionally active chromatin tends to have short nucleosome repeat lengths is strengthened by studies of active genes within metazoan genomes (5Berkowitz E.M. Riggs E.A. Biochemistry. 1981; 20: 7284-7290Crossref PubMed Scopus (20) Google Scholar, 6Villeponteau B. Brawley J. Martinson H.G. Biochemistry. 1992; 31: 1554-1563Crossref PubMed Scopus (18) Google Scholar). Differences in the lengths of DNA that space the core nucleosomes are likely to have pronounced effects on core nucleosome structure as well as on higher order nucleosome packing arrangements (4Widom J. Annu. Rev. Biophys. Biomol. Struct. 1998; 27: 285-327Crossref PubMed Scopus (250) Google Scholar, 7Bash R. Lohr D. Progr. Nuc. Acids Res. Mol. Biol. 2001; 65: 197-259Crossref PubMed Google Scholar). Some years ago Simpson et al. (8Simpson R.T. Thoma F. Brubaker J.M. Cell. 1985; 42: 799-808Abstract Full Text PDF PubMed Scopus (374) Google Scholar) developed a DNA template composed of tandem sea urchin 5 S rDNA units. The basic 5 S unit can impose a nucleosome positioning preference. Concatamers of these units provide templates that allow the in vitro assembly of defined polynucleosomal arrays suitable for biophysical and biochemical studies. Concatamers of 208-bp 5 S units, e.g. the dodecameric array of units referred to as the 208-12, have been the most widely used, to study nucleosome positioning (9Dong F. Hansen J. van Holde K. Proc. Natl Acad. Sci. U. S. A. 1990; 87: 5724-5728Crossref PubMed Scopus (169) Google Scholar, 10Meersseman G. Pennings S. Bradbury E. J. Mol. Biol. 1991; 220: 89-100Crossref PubMed Scopus (109) Google Scholar), the in vitro nucleosome assembly process (11Hansen J. Van Holde Lohr D. J. Biol. Chem. 1991; 266: 4276-4282Abstract Full Text PDF PubMed Google Scholar, 12Hansen J. Lohr D. J. Biol. Chem. 1993; 268: 5840-5848Abstract Full Text PDF PubMed Google Scholar), chromatin folding, and its relationship to acetylation, linker histone presence, and transcription factor binding (13Hansen J. Ausio J. Stanik V. van Holde K. 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Biochemistry. 1999; 38: 2514-2522Crossref PubMed Scopus (70) Google Scholar, 22Sendra R. Tse C. Hansen J.C. J. Biol. Chem. 2000; 275: 24928-24934Abstract Full Text Full Text PDF PubMed Scopus (38) Google Scholar). The 5 S templates were made with a choice of DNA lengths between the basic positioning sequences (8Simpson R.T. Thoma F. Brubaker J.M. Cell. 1985; 42: 799-808Abstract Full Text PDF PubMed Scopus (374) Google Scholar),e.g. 172-12, 190-12, and 208-12, thus creating templates that effectively differ in average nucleosome repeat length. The 172-12 provides a model for short linker length chromatins like yeast, and the 208-12 provides a model for long linker length chromatins such as chicken erythrocyte. To analyze the fundamental features of nucleosome occupation on these multisite 5 S arrays, our labs have recently turned to atomic force microscopy (AFM). AFM is a powerful imaging technique that can be used to visualize a number of nucleic acid and nucleoprotein complexes (Refs. 23Lyubchenko Y.L. Jacobs B.L. Lindsay S.M. Stasiak A. Scanning Microsc. 1995; 9: 705-727PubMed Google Scholar and 24Lyubchenko Y.L. Gall A.A. Shlyakhtenko L.S. Methods Mol. Biol. 2001; 148: 569-578PubMed Google Scholar and references therein), including chromatin (25Allen M.J. Dong X.F O'Neill T.E. Yau P. Kowalczykowski S.C. Gatewood J. Balhorn R. Bradbury E.M. Biochemistry. 1993; 32: 8390-8396Crossref PubMed Scopus (86) Google Scholar, 26Leuba S. Yang G. Robert C. Samori B. van Holde K. Zlatanova J. Bustamante Proc. Natl. Acad. Sci. U. S. A. 1994; 91: 11621-11625Crossref PubMed Scopus (212) Google Scholar, 27Martin L. Vesenka J. Henderson E. Dobbs D. Biochemistry. 1995; 34: 4610-4616Crossref PubMed Scopus (47) Google Scholar, 28Fritzsche W. Henderson E. Scanning. 1997; : 1942-1947Google Scholar, 29Sato M. Ura K. Hohmura K. Tokumasu F. Yoshimura S. Hanaoka F. Takeyasu K. FEBS Letters. 1999; 452: 267-271Crossref PubMed Scopus (52) Google Scholar, 30Yodh J. Lyubchenko Y. Shlyakhtenko L. Woodbury N. Lohr D. Biochemistry. 1999; 38: 15756-15763Crossref PubMed Scopus (42) Google Scholar). It offers particular advantages for the type of investigation described here. The ability to directly visualize individual molecules allows one to count precisely the numbers of nucleosomes present on DNA templates. By analyzing many molecules, it is possible to determine unambiguously the population distribution, in essence the statistical distribution of nucleosome occupation states for the template, as a function of nucleosome loading, in modified versus unmodified chromatin, etc. The experimental results can then be compared with theoretical models for insight on how nucleosomes choose to occupy these arrays. Subsaturated arrays, i.e. arrays in which the number of available 172- or 208-bp nucleosome-binding sites exceeds the number of nucleosomes available to bind, are particularly useful for these types of studies because of the occupancy choices available to nucleosomes loading onto such templates. Subsaturated arrays also have intrinsic interest as models for specific chromosomal regulatory regions like replication origins (31Sogo J.M. Stahl H. Koller T. Knippers R. J. Mol. Biol. 1986; 189: 189-204Crossref PubMed Scopus (260) Google Scholar, 32Lohr D. Torchia T. Biochemistry. 1988; 27: 3961-3965Crossref PubMed Scopus (26) Google Scholar) and gene promoters (33Lohr D. Nucleic Acids Res. 1984; 12: 8457-8479Crossref PubMed Scopus (51) Google Scholar, 34Lohr D. J. Biol. Chem. 1997; 272: 26795-26798Abstract Full Text Full Text PDF PubMed Scopus (52) Google Scholar), which are often not fully saturated with nucleosomes. Previously, we determined the population features for subsaturated 208-12 arrays (30Yodh J. Lyubchenko Y. Shlyakhtenko L. Woodbury N. Lohr D. Biochemistry. 1999; 38: 15756-15763Crossref PubMed Scopus (42) Google Scholar). In this work, the population distributions for subsaturated 172-12 arrays are determined, and the results are compared with the 208-12 results. The 172-12 is a very important template because it provides a model for organisms with short genomic repeats and for transcriptionally active and newly assembled chromatin, which also tend to have short nucleosome repeat lengths (3Van Holde K. Chromatin. Springer-Verlag New York Inc., New York1988Google Scholar, 5Berkowitz E.M. Riggs E.A. Biochemistry. 1981; 20: 7284-7290Crossref PubMed Scopus (20) Google Scholar, 6Villeponteau B. Brawley J. Martinson H.G. Biochemistry. 1992; 31: 1554-1563Crossref PubMed Scopus (18) Google Scholar). However, despite its obvious interest as a model for these functionally important chromatins, the 172-12 has not been systematically analyzed except to determine that its folding (13Hansen J. Ausio J. Stanik V. van Holde K. Biochemistry. 1989; 28: 9129-9136Crossref PubMed Scopus (196) Google Scholar) and nucleosome positioning characteristics (9Dong F. Hansen J. van Holde K. Proc. Natl Acad. Sci. U. S. A. 1990; 87: 5724-5728Crossref PubMed Scopus (169) Google Scholar) resemble those of the 208-12. Thus, our analysis provides novel structural studies that can serve as the basis for further analyses and applications of this important model system. Histone acetylation is a provocative and much studied chromatin feature that is associated with both transcription and replication (35Jeppesen P. Turner B.M. Cell. 1993; 74: 281-289Abstract Full Text PDF PubMed Scopus (600) Google Scholar, 36Braunstein M. Rose A.B. Holmes S.G. Allis C.D. Broach J.R. Genes Dev. 1993; 7: 592-604Crossref PubMed Scopus (714) Google Scholar, 37Brownell J. Allis D. Curr. Opin. Genet. Dev. 1996; 6: 176-184Crossref PubMed Scopus (469) Google Scholar). Because of the link between histone acetylation and these functionally important chromatin states and because yeast histones are known to have high levels of acetylation in vivo (38Davie J. Saunders C. J. Biol. Chem. 1981; 256: 12574-12580Abstract Full Text PDF PubMed Google Scholar, 39Waterborg J.H. J. Biol. Chem. 2000; 275: 13007-13011Abstract Full Text Full Text PDF PubMed Scopus (88) Google Scholar), we also analyzed hyperacetylated 172-12 reconstitutes. The plasmid (p5S172-12) containing the 172-12 was a generous gift of J. Hansen. DNA and acetylated or nonacetylated HeLa histones were prepared as described previously (30Yodh J. Lyubchenko Y. Shlyakhtenko L. Woodbury N. Lohr D. Biochemistry. 1999; 38: 15756-15763Crossref PubMed Scopus (42) Google Scholar). Nucleosomal arrays were reconstituted at various subsaturating levels following the method of Hansen and Lohr (12Hansen J. Lohr D. J. Biol. Chem. 1993; 268: 5840-5848Abstract Full Text PDF PubMed Google Scholar) with some modifications. Briefly, HeLa histone octamers were mixed with 3 μg of the 172-12 DNA template at varying molar ratios of histone octamers to DNA. DNA and histone octamers were mixed together on ice at a final concentration of 2 m NaCl (plus TE (10 mm Tris-1 mm EDTA, pH 8.0)) and a final volume of 30 μl. Histone octamers were diluted in HSB buffer (2.5 m NaCl, 50 mm phosphate, pH 8.8, 1 mm phenylmethylsulfonyl fluoride) and added last to the reaction mix. Reaction mixtures were dialyzed (Spectra/Por 6–8 kDa) at 4 °C against 1 liter of TE containing 1 m NaCl for >12 h, 0.80 m NaCl for 3 h, and then 0.6 mNaCl overnight. The final dialysis step was against 1 liter of 1 mm EDTA (pH 8.0) for >12 h. Chromatin was fixed by dialyzing against fresh 0.1% glutaraldehyde in 1 mm EDTA (pH 8.0) for 6 h. Excess glutaraldehyde was removed by a final dialysis for 24 h against 1 liter of 1 mm EDTA (pH 8.0). Fixed samples were recovered and stored on ice until further use. To confirm that the reconstitutions were successful and to estimate their concentrations, an aliquot of each reconstitute was electrophoresed at 45 V on a native 3.5% polyacrylamide gel overnight at 4 °C. Oligonucleosomes migrate as a smear between free 172-12 DNA template and the gel well. The more nucleosomes the template contains, the slower it migrates. Those templates carrying ≥8 nucleosomes only minimally enter the gel. The samples for AFM were prepared as described (23Lyubchenko Y.L. Jacobs B.L. Lindsay S.M. Stasiak A. Scanning Microsc. 1995; 9: 705-727PubMed Google Scholar, 24Lyubchenko Y.L. Gall A.A. Shlyakhtenko L.S. Methods Mol. Biol. 2001; 148: 569-578PubMed Google Scholar, 40Lyubchenko Y.L. Gall A.A. Shlyakhtenko L.S. Harrington R.E. Jacobs B.L. Oden P.I. Lindsay S.M. J. Biomol. Struct. Dyn. 1992; 10: 589-606Crossref PubMed Scopus (151) Google Scholar, 41Lyubchenko Y.L. Blankenship R.E. Gall A.A. Lindsay S.M. Thiemann O. Simpson L. Shlyakhtenko L.S. Scanning Microsc. 1996; 10 (suppl.): 97-107Google Scholar). Briefly, immediately prior to deposition, chromatin samples were diluted 5–100-fold with 1 mm EDTA (pH 8). Ten microliters of the sample (DNA concentration, 0.2–0.4 μg/ml in 1 mm EDTA, pH 8.0) was pipetted onto pieces of AP-mica for 2 min, rinsed with deionized water (ModuPure Plus, Continental Water System Corp., San Antonio, TX), and argon-dried under vacuum. From a spread of 2–4 ng of DNA, one can count as many molecules as needed. The AFM images were taken in air with a MultiMode SPM instrument equipped with E-scanner (Digital Instruments, Inc., Santa Barbara, CA) operating in TappingMode. NanoProbe TESP probes (Digital Instruments, Inc.), conical sharp silicon tips (NCH, Nanosensor), and V-shaped silicon cantilevers from K-Tek International, Inc. were used for imaging. The typical tapping frequency was 300–340 kHz for TESP tips and 340–380 kHz for the K-Tek probes; the scanning rate was 2–3 Hz. For each reconstituted sample, 150–400 molecules were analyzed. "Countable" molecules were those that had easily discernible nucleosomes and discernible DNA ends. They could be either extended or more compacted. We also counted molecules containing closely contacting nucleosomes so long as we could be certain, by measuring widths for example, of the number of nucleosomes present. We observe a much higher incidence of closely contacting nucleosomes in the 172-12 samples than were observed previously in the 208-12 samples (30Yodh J. Lyubchenko Y. Shlyakhtenko L. Woodbury N. Lohr D. Biochemistry. 1999; 38: 15756-15763Crossref PubMed Scopus (42) Google Scholar). This feature presumably reflects increased internucleosomal contact resulting from the shorter nucleosomal spacing and will be analyzed thoroughly in another publication. 2R. C. Bash, J. Yodh, N. Woodbury, and D. Lohr, manuscript in preparation. Nucleosome population distributions were obtained by plotting the fraction of molecules with a given number of nucleosomes (n)versus n. Distributions for nonacetylated and hyperacetylated samples ranged from n av < 2 ton av ≅ 11. n av is the average number of nucleosomes present on the templates in a sample distribution. The following equation is used to calculaten av. nav=∑112n×(no.of molecules withnnucleosomes)total no.of molecules countedEq. 1 The error bars for each point in the distribution are calculated according to the following equation. error=no.of molecules with n nucleosomesno.of molecules with n nucleosomes×(Fr)Eq. 2 where Fr is the fraction of molecules with a particular number of nucleosomes, i.e. n. The experimental nucleosome loading distributions from AFM analysis were compared with theoretical distributions calculated, for the same average number of nucleosomes (n av), by assuming that nucleosomes bind randomly and with equal frequencies to each of the twelve 172-bp sites, regardless of the histone octamer to DNA ratio. For the theoretical (random) distributions, the fraction of DNA fragments with n nucleosomes bound (F n) is given by Equation 3. Fn=nav12n1−nav12(12−n)12!(12−n)!n!Eq. 3 Note that n av/12 is the random probability that any particular nucleosome site is occupied. Thus, (n av/12)n(1 −n av/12)(12 −n)is simply the total probability that any given arrangement ofn nucleosomes will exist, and 12!(12 −n)!n ! is the total number of arrangements, assuming that nucleosomes are indistinguishable. 172-12 DNA templates were reconstituted with various subsaturating levels of HeLa histone octamers to obtain a series of subsaturated chromatin samples. Each sample was imaged by AFM. A representative field is shown in Fig. 1. In each field, we counted the number of nucleosomes on every molecule in which all of the nucleosomes were clearly distinguishable, including molecules containing closely contacting dimers or trimers (Fig. 1,arrows), so long as we could be certain of the number of nucleosomes present. For each reconstituted sample, the population distribution, i.e. the plot of the fraction of molecules containing n nucleosomes as a function of n, and the n av, the average number of nucleosomes per template (see "Materials and Methods"), were determined. One of the powerful features inherent in the AFM approach is the ability to determine unambiguously the numbers of nucleosomes on template DNA molecules. Fig. 2 plots the relationship between the input histone level during reconstitution and the average number of nucleosomes (n av) loading onto 172-12 templates. For both acetylated and unacetylated chromatins, the n av increases smoothly with increasing input histone, showing a linear dependence at low n avbut becoming nonlinear at higher values. However, at all input histone levels, higher amounts of hyperacetylated than unacetylated histones are required to achieve a particular n av. Thus, it is apparently more difficult thermodynamically for hyperacetylated nucleosomes to assemble on these templates, at any loading level, indicating that acetylation of the N-terminal tails affects some facet of the occupation process on these templates. A study using a somewhat different experimental material, fully saturated 208-12 arrays (analyzed by restriction digestion), observed no apparent effect of acetylation on saturated loading (20Tse C. Sera T. Wolffe A. Hansen J. Mol. Cell. Biol. 1998; 18: 4629-4638Crossref PubMed Scopus (482) Google Scholar). We have not analyzed saturated arrays by AFM methods because nucleosomes are too difficult to count unambiguously on such templates (30Yodh J. Lyubchenko Y. Shlyakhtenko L. Woodbury N. Lohr D. Biochemistry. 1999; 38: 15756-15763Crossref PubMed Scopus (42) Google Scholar), but we do observe that loading curves for subsaturated 208-12 templates remain linear to highern av values than for 172-12 templates, which results in a higher average nucleosome occupancy per input histone at higher subsaturated levels (nav > 9) on the 208-12. 3J. Yodh, Y. Lyubchenko, L. Shlyakhtenko, N. Woodbury, and D. Lohr, unpublished results. We suggest that this difference in loading response reflects a repeat length difference between the two templates. Other repeat length-dependent differences will be described below. Our limited data at very low input histone suggests that the plot may have a nonzero intercept (Fig. 2). One possible explanation for such behavior is a "threshold" effect, i.e. a certain level of histone must be present before nucleosomes begin to appear on the DNA templates. This would probably reflect trivial features, such as the need to saturate binding sites on the dialysis tubing, and in agreement with that suggestion, the curves for both types of 172-12 arrays (Fig. 2) and for 208-12 chromatin (not shown) would extrapolate to the same threshold value. Because AFM only needs subnanogram quantities of material, we routinely reconstitute 3 μg of DNA, and thus, at low n av values, there are only nanogram quantities of histones. Reconstituting larger amounts of material (20Tse C. Sera T. Wolffe A. Hansen J. Mol. Cell. Biol. 1998; 18: 4629-4638Crossref PubMed Scopus (482) Google Scholar) could probably avoid this type of behavior. A nonzero intercept would have no consequence for the major feature of Fig. 2, the consistent difference in occupation level between nonacetylated and acetylated arrays, nor for the results to be presented below, which are all based on direct visualization and counting of nucleosomes on DNA templates and thus would be unaffected by such behavior. Moreover, it is possible that the response at low input histone is actually asymptotic, which would make the curves sigmoidal in shape and characteristic of cooperativity. Analysis of nucleosome location data provides a more sensitive way to test for cooperativity and, indeed, using such an analysis, we have detected cooperativity in occupation on 208-12 templates. 4J. Yodh, et al., submitted for publication. 172-12 locational analyses have not been completed.2 Analysis of population distributions provides more detailed information about the nucleosome occupation of these multisite arrays. A representative set of population distributions that span the range from low loading (lown av) to high loading (highn av) for 172-12 templates reconstituted with nonacetylated histones is shown in Fig. 3(A–D, closed circles with solid lines). The error bars shown depend on the number of molecules counted at each value of n and are calculated as described under "Materials and Methods." For each experimentally determined distribution in Fig. 3, we also show the distribution that would be produced by a random process (dotted lines), calculated for the same n av. A random process assumes random and equivalent binding of nucleosomes to each of the 12 sites on the DNA template, with no binding site preferences or site-site interactions of any kind. The equation used to calculate these theoretical (random) distributions is given under "Materials and Methods." These representative data demonstrate several characteristic features of subsaturated 172-12 nucleosomal array populations. First, it is clear that reconstitution at any subsaturating level yields a discrete population of (subsaturated) molecules. For example, at least 70% of the molecules are found within a span of ±2 nucleosomes around the peak species in any distribution. With increasing loading, the distributions shift progressively to a highern av value but remain discrete. Thus, polynucleosomal occupation of these templates is multi-state in nature,i.e. it involves stable, partially loaded intermediates and therefore is not highly cooperative. The type of behavior demonstrated in Fig. 3 was previously observed for the larger repeat size 208-12 nucleosomal arrays, whether analyzed by AFM (30Yodh J. Lyubchenko Y. Shlyakhtenko L. Woodbury N. Lohr D. Biochemistry. 1999; 38: 15756-15763Crossref PubMed Scopus (42) Google Scholar) or sedimentation analysis (12Hansen J. Lohr D. J. Biol. Chem. 1993; 268: 5840-5848Abstract Full Text PDF PubMed Google Scholar). Second, the distributions vary somewhat with the nucleosome occupation level. At low (n av 8) loadings, the distributions are featureless and closely resemble random distributions (Fig. 3,A and D). However, in distributions from samples in the mid-range of occupation, n av = 4–8 on these 12-site arrays, there are specific features that indicate deviations from random behavior (Fig. 3, B and C). Perhaps the most obvious of these is a deficit (compared with random expectation) in the fraction of molecules with one nucleosome fewer (Fig. 3 B) or more (Fig. 3 C) than the major peak value in the distribution, a feature that causes secondary maxima, i.e. shoulders, to appear at ±2 nucleosomes from the major peak. This n avdependence is quite repeatable. Virtually all of the distributions at low ( 8) n av closely follow a random curve, and none of them shows a +1 or −1 deficit or a secondary maximum, whereas all of the mid-range (n av = 4–8) distributions show these features to some degree, and none follows a random curve (not shown). Moreover, the features appear and then disappear, respectively, in a fairly narrow range aroundn av = 4 and n av = 8. Thus, the ±1 deficit appears to be limited rather specifically to the mid-range of loading. For a more stringent test of the generality of the mid-range features, the data from all of the nonacetylated 172-12 chromatin samples in then av = 4–8 range was pooled (Fig.4 A). To make this compilation, the most populated n value in each sample distribution,i.e. the n value with the largest fraction of molecules in the distribution (designated "0"), and the fractions of molecules containing 1, 2, 3, or 4 nucleosomes fewer (−) or more (+) than that n value are tabulated. The 0, ±1, ±2, ±3, etc. classes from each of the various sample distributions are then summed together and displayed as a single profile (Fig. 4 A). This type of analysis allows all of the various distributions to be combined into a single data set, thus identifying features that are generally characteristic of the entire set of mid-range samples. The composite profile shows a statistically significant depletion of molecules containing one nucleosome fewer and one nucleosome more than the major peak (Fig. 4 A), confirming that this specific deficit at ±1 in the distribution is a general feature of nonacetylated 172-12 arrays in the mid-range of loading. The appearance of shoulders at ±2 nucleosomes from the peak is clearly due to the depletion of the ±1 classes because the shoulders are present at approximately the random expectation level. Thus, the occupation process for these mid-range arrays includes a component(s) that creates a dispreference for molecules containing one nucleosome more or less than the peak value in the distribution. Note that this is not a dispreference for odd numbers of nucleosomes on the template (data not shown). Rather it is a dispreference for molecules that contain one nucleosome more or less than the peak n value, whether that peak value is even or odd. Based on the magnitude of the deviations from random, we estimate that there are ∼20% fewer molecules present in each of the ± 1 classes than a random process would be expected to produce (Fig. 4 A). Thus, the effect responsible for this nonrandom behavior is probably only one contribution to the template loading process. However, the existence of any such tendency is a novel observation and is probably only detectable by an analysis that can determine precise population distributions, like AFM. The distributions for samples in the mid-range of loading are also broader than random expectation. In the composite pro